EGEE'06

Video message

The goal of the introduction is to define the goals of the 
workshop

This first talk of the workshop aims at introducing the 
gLite data management services and to open a first 
discussion

The goal of this talk is to shortly present the project 
and to introduce the project needs in terms of data 
integration

The goal of this talk is to shortly present the project 
and to introduce the project needs in terms of data 
integration

The goal of this talk is to shortly present the project 
and to introduce the project needs in terms of data 
integration

This introduction will describe the changes in the NA3 
activity in phase 2 of the EGEE project, introduce new 
partners and highlight changes in the approach to 
training provision in this phase.

This talk will demonstarte use of the EGEE digital library 
for accessing and reusing course materials. It will alsso 
describe the work of the Editorial Task Force (ETF) in 
reviewing archive course materials and recommending 
those which are particularly suitable for re-use when 
running future training events.

This contribution will describe experience of running 
Grid training events in the Swiss/German Federation, 
focussing particularly on market demand and market 
readiness.

This session will include brief reports from activity 
partners on progrees of EGEE training in their areas.

We will wrap up the session by inviting discussion on 
themes of interest - including:

 - Communications between activity partners
 - Overall Activity Metrics and Partner Metrics
 - Reporting requirements/Feedback
 - eLearning digital library and ETF
 - t-infrastructure provision
 - Impact of gLite3 changes on training

This talk will explain how the EGEE project works with
business and industry as well as the mechanisms it has
defined to allow commercial organisations to get involved. A
look to the future beyond the current project will also be
included.

Abstract: The talk introduces the audience to the 
European Union (EU) research policies, focusing in the 
area of Research Infrastructures. It outlines the historic 
evolution of the constituency of electronic 
Infrastructures (eInfrastructures) as these become 
mature. In this process, the progressively increasing 
role of industry is analysed. The main eInfrastructures 
topics in the 7th EU Framework Programme (FP7) 
Connectivity, Grids, Supercomputers and Scientific 
Repositories are outlined, and the participation of 
industry in upcoming FP7 calls is encouraged.

Grid Computing has come a long way since its inception in
the academic area; the dynamic, transparent, and secure
access to a variety of computing, data and network resources
makes it a very attractive proposition for use in industrial
and general Enterprise contexts. The talk discusses how to
facilitate the uptake of Grid technology with Enterprises
for technical and general business computing. It touches on
the role of standards, the need for integration with
existing Enterprise IT ecosystems and on how to leverage new
platform﷓level technology in future Grid systems.

Similarities and differences between Grid deployments in
research and industry are described and assessed.  The
status of the present situation is described from a global
perspective.  An attempt will be made to project the
potential future evolution of grids in research and industry.

The goal of this round table is to identify issues 
relevant to data integration which are raised by the 
different Healthgrid projects and which could be 
better handled through a collaboration with EGEE

Grids in industry must respond to business drivers and
exigencies.  Grids are part of the global evolution of
corporate information technology.  This means that corporate
grids have to be seen in the context of major IT trends like
virtualization, standardization, and the building of
service-oriented architectures.  The corresponding forces
and consequences are described, as well as observed benefits
of grid deployments in industry.

GS1 is a not-for-profit organisation that develops global
standards for the unique identification of goods and
services with offices in 104 countries around the world. The
GS1 system consists of a set of complementary standards and
solutions that in combination allows for streamlined supply
and demand chain from manufacturer to end users. Physical
goods and products are marked with barcodes or RFID tags,
business information is exchanged using UN/EDIFACT or XML
based messaging standards and Internet based networks are
used for master data alignment and supply chain event
management.
The aim of this presentation is to describe these standards
and solutions as they are applied today as well as future
development. The focus will be on information sharing and
communication. This can then serve as a basis for a
discussion on whether Grid technology could be applicable
and, if so, what questions need to be resolved, such as
security, authentication, investments and migration path.

The main objective of the Business Experiments in Grid
(BEinGRID) projectis to foster the adoption of the so-called
Next Generation Grid technologies by the realization of
several business experiments and the creation of a toolset
repository of Grid middleware upper layers.

BEinGRID will undertake a series of targeted business
experiment pilots designed to implement and deploy Grid
solutions in a broad spectrum of European business sectors
(entertainment, financial, industrial, chemistry, gaming,
retail, textile, etc).

Eighteen business experiments are planned in the initial
stage of the project with a second open call for proposals
in the latter stages. Secondly, a toolset repository of Grid
service components and best practise will be created to
support European businesses that wish to take-up the Grid.
To minimise redevelopment of components, BEinGRID will
deploy innovative Grid solutions using existing Grid
components from across the European Union and beyond.

Is the Grid providing new issues and challenges on
information security? Computational ressource theft is
occurring in lots of institutions and is nowadays causing
very limited liability issues, but much more obvious
performance issues. Grid computational ressource theft, if
occuring would cause tremendous liability issues, for the
ressource provider and the ressource requester. A high
implication on organisational, procedural as well as legal
and ethical aspects would be caused. The purpose of this
session is to provide a business analytical perspective of
the strengths, weaknesses, opportuntities and threats of
what could be some of the issues related to Grid security.
Indicate how Grid connected institutions would need to deal
with these issues. Demonstrate how malicious individuals or
organisations could make use of the Grid to deploy massive
cyber information attacks. Rather than take the common “head
in the sand” approach to world interconnected networks
problems, this session presents a proactive business,
technical and legal look at protecting Grid assets and Grid
ressources against cyberattackers. Putting things in
perspective by looking at the threats, delegates will be
presented with comprehensive ideas that offer defence before
disputes arise, and pragmatic advice on resolution if they do.

The EGEE grid infrastructure see daily use by scientists 
from a sizable number of diverse disciplines.  The large, 
production use reveals common access patterns which 
transcend individual scientific disciplines. 
Moreover, it suggests what common grid functionalities 
will be required in the near future.  This talk classifies 
and characterizes the applications currently seen on the 
EGEE grid infrastructure and tries to foresee what 
additional services EGEE will need to provide in the 
future.

Large scale Grid systems such as EGEE, TeraGrid, 
NAREGI and others are designed to radically change the 
paradigm of scientific problem solving.  They enable 
multidisciplinary teams, distributed around the globe, to 
share ideas, applications and data to solve problems at 
scales not previously considered possible.   To 
accomplish this objective we have built a substantial 
middleware infrastructure (Globus, g-Lite, OGSA) that 
provides us with the core foundation of capabilities and 
services that support security, computation 
virtualization and data virtualization.  Unfortunately, 
these services alone do not provide a platform for 
engaging the large majority of potential scientific and 
industrial users.  They are simply too complex and, by 
their nature, too unreliable to use except for a small 
community of Grid experts.   To engage the vast 
majority of potential users of Grids a category of tools 
and services, know in the TeraGrid project as Science 
Gateways, is emerging.  They are built around web 
portal and desktop client technology and provide a layer 
of abstraction providing data and computational 
services in a language that is easily cast in terms of 
specific scientific domain languages.  Portals like Genius, 
GridSphere and the Open Grid Computing Environment 
(OGCE) are being deployed for many scientific domains 
including bio-science, chemical informatics, astronomy, 
earth sciences, nano-technology and many industrial 
applications.  This talk will examine the core services 
provided by these gateway tools including personal 
metadata catalogs, workflow tools, graphical user 
interfaces, and data provenance and publication 
services.   We will look at what works and  describe 
where we still need more research in  the future.

This slot will introduce the NGI policy workshop, which is a
milestone of the EGEE NA5 activity (Policy and International
Cooperation). It will identify the scope and expected result
of the session.

This session will provide input on the next EC calls of the
Capacities - Research Infrastructures related to the NGIs/EGIs.

This presentation focuses on aspects such as exploitation
and sustainability of huge public investments in computing
and communication infrastructures.
In order to fully justify research activities and to promote
their adoption at the production level, industries and
public administration should be involved and fully motivated
in approaching new and more effective technological
solutions. The PI2S2 project, currently under development in
Sicily, represents one concrete attempt to develop a new
GRID computing infrastructure at the regional level,
involving research institutions, public administration,
industries and SMEs as potential users. Since the very
beginning particular attention has been devoted in
coordinating all the development activities with the
requirements coming from SMEs that, strictly cooperating
with the research institutions involved, are proposing and
“bringing into the GRID” their specific needs. Synergy
between academy and SMEs is a fruitful approach with mutual
benefits for both participants and big impact on the future
sustainability of the investments.

Faced with the challenges of streamlining and efficiency,
CERN has recently implemented a leading-edge e-procurement
solution which generates savings by automating the high-cost
business processes previously associated with recurrent
low-value purchases. The solution, which benefits both the
supplier & the customer, is rapidly expanding and we observe
significant interest in other large organisations following
suite. The challenge now is to create a vision for SME
participation (both as suppliers and/or customers) and
question if emerging grid technologies may provide a canvass
for such a picture.

The presentation will cover:

SMEs: Describing the Grid environment developed for 
European Pole of Plasturgy and on the business model 
adopted.

CNES (French Space Agency): Intraned grid prototype 
based on gLite.

Fusion: Actions have been begun by CS SI with the 
TORE SUPRA CEA team and contact with the ITER 
project team, aimed at promoting the use of Grids by 
the fusion community. CS SI is pushing the idea of 
a “Grid hub portal” allowing the users to submit jobs on 
super computer infrastructure and also doing pre and 
post processing on EGEE.

Our research showed that British SME consider Grid as a valuable
instrument for achieving their business objectives. The TME
report includes a number of business cases which demonstrate how
Grid could help small companies to do new things and improve
performance. However, opportunities for SME to benefit from Grid
technologies are limited by the following factors:
• Lack of infrastructure
• Lack of skills
• Cost of ownership

The main objective of this project is to find out how EGEE and
other scientific grid projects could help SME to overcome the
abovementioned difficulties and help companies to adopt Grid.

The architecture of the computational Grid has been
thoughtfully engineered to achieve a high degree of
dependability: quality services must always be available
even if the presence of faults in the system may have a
significant probability. We identify that, in the Grid
architecture at present, the QoS in dependability is at the
cost of a compromised trustworthiness.

The compromise can in fact reduce or even nullify the very
service of dependability if the Grid technology is deployed
in a default setting of non-collegial environment. We
present the work of the Daonity Project and discuss how
Trusted Computing technologies can be applied to maintain
QoS for both dependability and trustworthiness for the Grid.
Daonity is an Open Grid Forum Project attempting to  improve
Grid Security Infrastructure using Trusted Computing
technologies.

Grid Computing Now! is a Knowledge Transfer Network (KTN)
project run as part of the UK Government's DTI Technology
Programme. The aim of the Technology Programme is to promote
the adoption of key technologies to improve UK economic
development. Grid Computing Technologies are one such
example having received a substantial amount of research
duning in the past 6 years or so. The aim of the KTN is to
capitalise on this learning and transfer knowledge about
Grid Computing Technologies to UK Public and Private sector
organisations who may benefit from its adoption. This
presentation will describe the plan and key activities of
the KTN, revealing some of its initial learnings as it
reaches the half-way point. The key areas of interest and
enthusiasm of the marketplace will be described, as will the
more strategic attempts to engage Public sector
organisations in considering the case for change. As the
Technology Programme matures, several KTNs are combining
their resources to address larger governmental challenges,
there is considerable interest in the area of Intelligent
Transport; e-Enabled infrastructure for collaboration and
the potential to provide breakthroughs in Healthcare
administration and treatment. There have been several
Collaborative R&D Projects founded in these areas and this
project is seen as a vehicle to champion their technology
contributions.

Use of eCommerce tools which allow public sector buyers and
sellers to trade over the internet is growing rapidly,
driven by the EU targets.  The i2010 targets state that “by
2010 all public administrations across Europe will have the
capability of carrying out 100% of their procurement
electronically, thus creating a fairer and more transparent
market for all companies independent of a company’s size or
location within the single market.”  Countries such as
Denmark and Sweden have or are implementing regulation that
require suppliers to the public sector to submit invoices
electronically.  What has been the experience in the UK of
implementing these systems and what are the concerns of
public administrations and suppliers connecting on these
types of systems which would have to be overcome by any
potential solution using Grid Computing?

Public Administration in the forms of Government
Departments, Non Departmental Public Bodies (NDPB’s) and
International Non Governmental Organisations (NGO’s) invest
significant moneis in new technology, new solutions and new
service delivery resources. 
This session will identify current drivers at domestic and
international levels.

As part of the GridAlliance, Brunel University is producing
Desktop Grid systems that are being successfully used to
reduce the take taken to turn around complex decisions. 
This presentation gives an overview of our general approach
and examples of how it has been used to support decision
making applications in the public sector, manufacturing and
finance.  For more information visit www.gridalliance.co.uk.

The progress made in the implementation of the Grid enabled
Molecular Simulator
(GEMS) and the activities of the CompChem VO are presented.

Today's computing and storage requirements make EGEE Grid a perfect platform for
chemistry applications [1]. Despite the fact that a few quantum chemical codes have
been successfully ported to the Grid [2] there is still lack of commercial chemical
software that would be available for whole EGEE community. The main reasons blocking
wide use of commercial software are its license requirements.  Confirmation of
fulfilling the license requirements is the key step in porting software to the Grid
and than using it. 

There are many computational packages available nowadays for chemists. Among them the
most popular for its easiness of use, large number of computational methods and
constant development during the last thirty years is the Gaussian package [3,4]. The
advantages of Gaussian make it an excellent choice for our application. Moreover,
enabling to use the Gaussian package on the Grid by wider community will benefit not
only in chemistry but also in biochemistry, medicine and even physics. 

In this report we would like to share our experience in enabling commercial software
on the Grid using Gaussian program [5] as an example. In such a case access to the
software is influenced by additional license requirements. Therefore, in order to
meet these requirements, a new virtual organization (VO) gaussian has been created.
Membership in gaussian VO enables user an access to Gaussian package operated and
maintained by ACC Cyfronet AGH. The access to Gaussian package suite is open for each
EGEE Grid user who does have a valid certificate and agrees to obey Gaussian, Inc.
license requirements. 


Presented installation procedure may be used to make available other commercial
software for EGEE community.

References;
1. EGEE web page http://www.eu-egee.org
2. GAMESS package on EGEE Grid: http://egee.grid.cyfronet.pl/gamess
3. W. J. Henre, W. A. Lathan, R. Ditchfield, M. D. Newton, J. A. Pople, Gaussian 70,
QCPE, 11, 236,1973
4. Gaussian web page: http://www.gaussian.com
5. Gaussian program on EGEE Grid: http://egee.grid.cyfronet.pl/gaussian

The applications team of the int.eu.grid project is dedicated to promote the use of
the  Grid for those demanding scientific applications involving interativity and
powerfull  visualization needs. 

Grid added value in the int.eu.grid project means not only porting the application to
a Grid infrastructure. It also implies to make profit of the development of an
interactive environment for job submission, providing powerful graphics and
visualization solutions. Being such services expensive from the point of view of
Network connectivity we need to define some measure of Quality of Service to asses
the reliability of the Network connection when facing this kind of challenges.

So far we have engaged a number of applications which cover different aspects of
needs in concerning the grid implementation of job submission, interactive steering,
and visualization. We have catalogued the applications according to four area groups:
High Energy Physics, Nuclear Fusion, Medical Applications and Environment. We have
also included a section regarding prospective new applications which are currently
under consideration, in particular collaborative environments with applications to
medical diagnosis and Astrophysics.

Context:
Centre of Excellence in Information and Communication
Technologies (CETIC) has a
cluster of the following specifications:

Number of Nodes: 38
Number of Processors: 74
RAM size: 160 GB
Disk storage: 10 TB 

This cluster will eventually be a part of the Belgian Grid.
CETIC is seeking
assistance from the EGEE project in the deployment and
administration of this Grid
platform.


Scientific Goals:
The Grid platform at CETIC will serve as a research test-bed
to support
experimentations, prototyping, simulations, and other
associated research activities.
The Grid platform will also be made accessible to companies
for testing and
benchmarking purposes.

	
Description:
As the Belgian Grid is going to switch from LCG-2 to gLite
middleware, CETIC Grid
will have to opt for the same middleware – gLite. The CETIC
Grid team's objectives
start from deploying a grid platform with a set of computing
resources to administer it.

Grid Added-value:
Besides Belgian Grid (BEgrid), CETIC is a partner of a
number of European projects
including Business Experiments in Grid (BEinGRID) [1] and
Highly Predictable Clusters
for Internet Grids (HPC4U) [2]. These projects require Grid
platform to facilitate
the experimentation of the envisioned pilot applications.

Potential User Community:
CETIC has active collaborations with Belgian companies and
universities. Moreover,
CETIC is involved in a number of European projects [3].
There will be a broad
spectrum of potential user community of CETIC Grid. It will
comprise of academics,
researchers, and industrial R&D teams.

EGEE Impact:
EGEE consortium has rich expertise in the deployment of Grid
platforms. gLite is the
middleware of the EGEE project. The experts from the EGEE
consortium are in the most
fortunate position to provide assistance in the deployment
and administration of a
gLite-based Grid platform.

Grid Services Needed:
It is difficult to quantify the set of Grid services sought
by the CETIC, as the
intended Grid platform will also be made accessible to
companies for testing and
benchmarking purposes and the required services will vary
for every experiment. In
other words, CETIC requires a comprehensive set of Grid
services for its activities.

Key Issues:
The key issues include the successful deployment of a Grid
platform, its
administration, and its integration with the Belgian Grid so
that experiments of the
Grid projects can be performed, CETIC’s and its partners’
researchers can prototype
and/or simulate their propositions. For example, prototyping
of secure fault tolerant
replica generation mechanism for Grid-based data management
systems [4]. The Grid
platform will also be made accessible to companies for
testing and benchmarking purposes.


References:
1. Business Experiments in Grid –  www.beingrid.com
2. Highly Predictable clusters for Internet Grid (HPC4U) –
http://www.hpc4u.org
3. CETIC Newsletter, January 2006 – 
www.cetic.be/article372.html 
4. Naqvi S., Massonet P., Arenas A., 'Security Requirements
Model for Grid Data
Management Systems', International Workshop on Critical
Information Infrastructure
Security 2006 (CRITIS'06), August 30 – September 02, 2006,
Samos Island, Greece

Edutain@Grid is an exciting and ground breaking new project making use of Grid
technology. The project will identify and define a new class of applications that are
highly significant for Grid computing but have not been studied in the past, which we
characterise as Real-Time Online Interactive Applications (ROIA). The distinctive
features that make ROIA unique include large user concurrency to a single application
instance, ad-hoc connections, competition-oriented Virtual Organisations, real-time
interactive response, dynamically changing control and data application flows whilst
maintaining high Quality of Service (QoS), user friendly security, and novel
Business-to-Consumer market models. In order to overcome these challenges, the
project team will develop a new middleware layer that will allow ROIA to exploit Grid
computing and validate the system using two pilot applications from online gaming and
e-learning domains. Edutain@Grid is expected to be of key interest to game developers
and publishing companies by tackling some current key industry challenges: (1) larger
user concurrency and high QoS ranging between 64128 players for fast action online
games to thousand of players in persistent Massively Multi-user Online Role Playing
Games (MMORPG); (2) standard API and scalable networks for cheaper integration and
online game hosting.

Similarly the benefits to the e-learning community are expected to be significant
where large numbers of geographically disparate students can interact with
instructors making use of large operational data sets. In particular this will be
relevant to online simulations in scientific modelling applications used in the
energy, defence, transport and legal market sectors. Furthermore Edutain@Grid is
expected to attract new developers and development ideas that were not previously
possible or simply cost prohibitive.

ArchaeoGRID community aims to show that the archaeology, by
deploying grid
technology, will increase in quality and quantity the
production, diffusion and use
of archaeological knowledge. 
For this purpose the selected archaeological case study has
been the origin of he
city in the Mediterranean area between XI and VIII centuries
B.C., that is a central
problem in modern archaeology. The approach of such problem
is based on landscape
archaeology methods extended to the large Mediterranean region.
The first application running on GILDA t-infrastructure is a
paleoclimatic simulation
based on MM5 mesoscale model and on geomorphological and
archaeological data related
with the studied period and region.
The ArchaeoGRID system also, merging different approach in a
single system and using
a service-oriented architecture, has been studied with the
help of GILDA and DILIGENT
Pisa groups.

This slot will present the summary of the questionnaire
responses received so far, collecting all national responses
in one presentation. This will act as input to stimulate the
discussion to follow. The final findings
will be documented in an EGEE deliverable scheduled for
November.

This session will highlight possible areas of convergence
and divergence and feed the discussion of the next slot,
which concerns the next steps to be taken.

This will be an open discussion on the next steps on the
path towards a European Grid Initiative. Forming an
Association of NGIs or an Association for the promotion 
of NGIs will be discussed. Note that a next workshop on 
EGI will be organised at the end of this year or the
beginning of next year.

As part of a study supported by EGEE, this analysis has
evaluated Grid adoption at Europe’s auto firms. It has
compared these findings to results from earlier studies of
Grid use in the auto industry in the US and Japan.

The study’s initial findings are that Europe’s automakers
have adopted Grids and are doing thousands of simulations a
day to support design, product development, and testing. In
at least one case, virtual cars are being used to manage
production.

One of the drivers for Grid deployment is the tremendous
cost savings they offer. Preliminary estimates from the
study suggest that during 2007-2010, auto firms will save
about 25% of production costs each year. This will be a
result of using Grids to support virtualized design and
product development and creating virtual cars for production.

European, American and Japanese auto firms are deploying
firm-wide Enterprise Grids at about the same pace, with most
firms expecting to have such Grids in place by 2009-2010.
Collaboration Grids with links to partner firms (Partner
Grids) are more evident in the US, but Europe and Japan will
deploy these more rapidly than US firms later this decade.

This preliminary analysis suggests that the IT-based model
of Grid adoption does not represent how auto firms are
adopting Grids. It suggests that Grid adoption is directly
linked to managing the complexity that results from being
able to use Grids. With thousands of simulations, auto firms
need higher-level management capabilities linked to Grids to
synchronize new findings with design models. With such
capabilities, including dynamic provisioning and feedback
mechanisms, Grid adoption would be faster.

A recent study from Gartner Group shows that computing
utilization of Intel platform is normally very low (from 15
to 30%). 
The use of an internal Grid computing infrastructure provides a
way to maximize the computing utilization of resources, lowering
cost and speeding some kind of processes.
Monte dei Paschi, one of the most important banking group in
Italy,  started studying this kind of architecture since
2004 and
set up a production environment in January 2005 for many
different computing intensive applications.
Today we forecast an evolution of our architecture for external
services and for a new kind of sourcing strategy in ICT.

Complex processes in highly heterogeneous and distributed
environments are a major challenge of industrial product
development and service provisioning. Those processes typically
involve a large number of independent organisational entities at
different locations as well as different applications and data
sources.
Based on the application and enhancement of grid technology,
this
challenge is targeted in the EU-funded SIMDAT project
[www.simdat.org]. SIMDAT focuses on four application areas:
product design in the automotive, aerospace and pharma industry
as well as service provisioning in meteorology. Within the first
half of the project important parts of this matrix of
technologies and application areas have successfully been
established.
Technologies for the distributed data access as well as semantic
technologies have been combined in order to provide an
environment which solves typical problems of heterogeneous
data-grids involving complex engineering tools in the automotive
area. This show-case demonstrates how the industrial production
en-vironments can benefit from synergies by the combination of
grid- and semantic technologies.

The presentation will look briefly at Total Exploration &
Production, high performance computing needs and the
different avenues that it is looking at to fulfill these
needs in the future. This presentation will focus on one of
these areas, External Grid Computing, and give an overview
of the current research project into External Grid Computing
that is taking place at Total's UK based Research Centre.
The research project involves porting an internal
application to the gLite middleware/ EGEE Infrastructure to
gain hands on experience and insight into the advantages/
disadvantages of External Grid Computing from Total's
perspective.

The Radiocommunication Bureau of the ITU (ITU-BR) managed
the preparation and the conduct of the ITU Regional Radio
Conference RRC06 to establish a new frequency plan for the
introduction of digital broadcasting (band III and IV/V) in
Europe, Africa, Arab States and former-USSR States. During
the 5 weeks of the RRC06 Conference (15 May to 16 June 2006)
delegations from 119 Member States negotiated the frequency
plan.

The frequency plan was established in an iterative way.
During week time at the RRC06 administrations negotiated and
submitted their broadcasting requirements to the ITU-BR and
the associated results of negotiation (sometime in terms of
several million records). The ITU/BR carried out over the
weekend, substantive validation and processing activities
and conducted all the calculations (analysis and synthesis)
that resulted in assigning specific frequencies for the
draft plan. The result of the calculations was distributed
to delegations at the beginning of the subsequent week and
served as input for the next round of negotiations, with the
last iteration constituting the basis for the final
frequency plan. In addition, partial calculations were
performed for parts of the planning area in between two
global iterations (for the entire planning area). 

For obtaining optimum planning of the available frequency
spectrum, two different software processes have been
developed by the European Broadcasting Union and they have
been run in sequence at the Conference by ITU/BR:
compatibility assessment and plan synthesis. The
compatibility assessment (which was very CPU demanding and
adapted to run on a distributed infrastructure) calculated
the interference between digital requirements, analogue
broadcasting and other services stations. The plan synthesis
assigned channels to requirements which could share the same
channel.

The limited time to perform the calculation called for the
optimization of the process.  The turnaround time to provide
a new set of results was a critical factor for the success
of the Conference. The EGEE grid greatly enhanced the ITU-BR
available resources, constituted by a 100 PCs client-server
distributed system developed within the ITU-BR.

The compatibility assessment consisted in running a large
number of jobs (some tens of thousands). Each job is
basically the same application running on different datasets
representing the parameters of radio-stations. One should
note that the execution time varied by more than 3 orders of
magnitudes (the majority of jobs needed only few seconds but
few jobs required many hours) depending on the input
parameters and could not be completely predicted. To cope
with this situation we decided to use a client-server system
called DIANE that allows run-time load balancing, access to
heterogeneous resources (Grid and local cluster at the same
time) and a robust infrastructure to cope with run-time
problems. In the DIANE terminology, a job is defined as a
“task”. DIANE allowed us to use in the most effective way
the available resources since in this system each available
worker nodes asks for the next task: while a long task will
“block” a node, in the mean time the short tasks (the large
majority) will flow through the other nodes.

We demonstrated to be able to perform the required
calculations on the EGEE/LCG infrastructure during
feasibility tests performed in November 2006 and we used
these techniques during the Conference in very close
collaboration with CERN. We were also able to integrate the
EGEE infrastructure with the ITU-BR distributed system at
the monitoring level, via the Caltech-developed product
MonALISA.

The EGEE infrastructure did not only enable us to give the
adequate support for an important international event but,
in addition, the substantial speed-up observed opened the
possibility to allow faster and more detailed studies during
the Conference. The technical improvement gave the
possibility to provide a better service and technical data
to the Conference’s delegates.

Our set up was well suited for this application. The
possibility to access resources from the grid and corporate
resources (which we have not exploiting) is very appealing
and should be interesting for other users. The possibility
to describe and execute more complex workflow (presently we
are using the system to execute independent tasks in
parallel) could increase the interest for the tools we have
been using.

Geant4 is a general purpose toolkit for simulating the
tracking and interaction of particles through matter. It is 
currently used in production in several particle physics
experiments (BaBar, HARP, ATLAS, CMS, LHCb), and it has 
also applications in other areas, as space science, medical
applications, and radiation studies. 
The complexity of the Geant4 code requires careful testing
of all of its components, especially before major 
releases (which happens twice a year, in June and December)
including detailed regression testing on complex 
configurations.
We describe the recent development of an automatic suite for
testing physical processes in high-energy 
calorimetry. The idea is to use a simplified set of hadronic
calorimeters, with different beam particles at, several 
beam energies, and comparing relevant observables with the
reference version of Geant4. Only those 
distributions that are statistically incompatible are then
printed out and finally inspected by a person to look for 
possible bugs. The suite is made of Python scripts, and
utilizes the "Statistical Toolkit" for the statistical tests 
between pair of distributions, and runs on the Grid to cope
with the large amount of CPU needed in a short period 
of time. The total CPU time required for each of these
Geant4 release validation productions amounts to about4 
CPU-years, which have to be concentrated in a couple of
weeks. The Geant4 team has already run four of them, 
starting in December 2004. From December 2005 they run as
Geant4 VO demonstrating the full involvement of 
Geant4 inside the EGEE communities. Several EGEE sites have
provided them with the needed CPU, and this has 
guaranteed the success of the production, arriving to an
overall efficiency rate of about 99%.
We report the Geant4 experience in using the Grid, and in
particular the results obtained during the last 
production (June 2006). During that production we used the
Ganga/Diane framework developed by the ARDA 
group at CERN was used for. the 10% of the production with
very promising results. The next production 
(December 2006) will be fully executed using this framework
and we present the present status of the 
preparation.

In the last 2 years, the ATLAS collaboration has been continuously running Monte
Carlo event simulation on the LCG/EGEE production grid. The ATLAS production system
is highly automated: jobs defined in a central database are handled by supervising
agents, submitted to and executed by the underlying Grid infrastructure. On the other
side, more recently the ATLAS Distributed Dada Management System also became fully
functional on EGEE. Such a system guarantees organization of data in a hierarchical
structure (datasets) and data distribution across sites via asynchronous file
transfer mechanisms. The ATLAS Production and the Distributed Data Management systems
have been now fully integrated on the EGEE infrastructure. Running the new framework
should improve the activity organization (production tasks assigned to specific
groups of tiers) and data distribution and availability (datasets automatically
aggregated in well defined computer centers). Data aggregation will be particularly
important for subsequent activities such as data analysis. This contribution provides
an architectural overview of the integrated system and a description of our
operational experience, showing the improvements in respect of the past, current
issues and possible future developments.

The Australian Nuclear Science and Technology Organisation (ANSTO) is constructing
Australia’s new 300 million Australian dollar (178 million euros) Open Pool
Australian Light-Water (OPAL) reactor for neutron scattering research.  Each neutron
beam instrument from OPAL will provide a graphical user interface, known as GumTree,
for performing data acquisition and online data analysis.  GumTree is an Eclipse RCP
based open sourced application which involves international collaboration with a
number of major neutron and X-ray facilities.  It is proposed that GumTree will
connect to the Grid infrastructure in near future for computational intensive data
analysis, via the DANSE framework.  The DANSE project from Caltech has been awards
11.97 million US dollar funding from the US National Science Foundation for providing
software on distributed data analysis of neutron scattering.  ANSTO also has a
long-term commitment on providing eResearch services to the neutron community, such
as archiving instrument raw data to the national grid, and gridifying existing
instruments with CIMA middleware.

The ATLAS and CMS experiments have extensively tested the gLite Workload Management
System by running real applications on the EGEE production infrastructure. This
allowed to study the behaviour of the system in a more realistic environment with
respect to the official certification infrastructure. This contribution describes the
work performed by the experiments on the gLite WMS and how this contributed to
improve its reliability and performance, thanks to a close collaboration with the
developers and the certification team of the EGEE project.

The 2006 data challenge – LHCb DC06 – is the final benchmark before the real 
data taking for validating the computing model and the infrastructure of LHCb 
and also a last opportunity for exercising the whole simulation chain on EGEE 
resources. For the past few years, LHCb has always been one of the top users 
of LCG resources gathering considerable experience in distributed computing at 
a large scale. The central part of the system is DIRAC (Distributed Infrastructure 
with Remote Agent Control), which is the experiment gateway to the Grid 
environment. The aim of this work is to present a preliminary experience from 
this ongoing DC06 and its goals, describing the DIRAC system, the 
performances achieved, and the problems observed.
The DC06 has started in August 2006 and it is expected to continue until the 
end of September. 
We will therefore describe the achievements and the plans for the continuation 
of this activity.

Traditional developments in Grid technologies have concentrated on providing batch
access to distributed computational and storage resources. The requirements to
access, control, and acquire data from widely networked distributed instruments
trigger the need to include a variety of new components. For instance, scientific
equipment like sensors and probes are a need in nowadays Grid infrastructures. This,
in turn, raises the need for supporting real-time operations and interactive work,
thus opening a new frontier of research and development in this field. 
The GridCC Project, launched in September 2004 by the European Union, addresses these
issues. The goal of GridCC is to exploit Grid opportunities for secure and
collaborative work of distributed teams to remotely operate and monitor scientific
equipment. In addition, GridCC will allow to exploit the Grid’s massive memory and
computing resources for storing and processing data generated by this kind of equipment. 
In this talk we present first the status of the GridCC Project, focusing then on the
real applications that have been equipped with our middleware. We have three main
running use cases, from the run control of a high energy physics experiments, to the
remote control and monitoring of a grid of small power generators and, finally, to
the far remote operation of a particle accelerator. Other applications that have
adopted our approach will be also presented; their field ranges from meteorology, to
education, to the control of the territory (geo-hazard) and to the remote control and
monitoring operations of telecommunication measurement equipment.  
Lastly, the integration with the gLite components will be highlighted, showing how
the services’ orchestration through a workflow engine has been introduced. Our
approach, based ontwo levels (namely, strict and loose) of guarantees to support and
monitor the real-time and interactive requirements will be also shown.

Scientists, as biologists or bioinformaticians, often deal with complex tasks
involving the integration of results from several computational tools and information
repositories that must be tied together in a coordinated way in order to automate the
execution of a set of analyses.

With the increasing number of databases and processing tools exposed as Web Services,
a workflow managing system able to operate according to the SOA standards is an
essential tool for e-Scientists to take full advantage of such resources. 

In a scenario where data sources and services are distributed and there is an
increasing request for computational power, special attention has been given to
workflows based on Grid services which
bring many attractive characteristics such as great efficiency, load balancing, fault
tolerance and reliability.

Making use of SOA principles, Grid-enabled workflows make Grid solutions more
transparent and supported on a wider range of platforms and environments, improving
interoperability among software applications.

Many tools have been developed for the composition and enactment of workflows for the
scientific community but most of today workflow management systems show great
limitations due to their intrinsic client-only nature.

Nice s.r.l. with EnginFrame /GENIUS  Grid portal/gateway realizes several
integrations of the Grid technology with the Web Services standards based SOA approach.

Addressing to e-Science community, Nice proposes a Grid-based solution that provides
basic building blocks for workflow construction. This solution both exposes services
as standard Web Services to be used within a client-side workflow engine (Taverna ),
and supports workflow enactment and life cycle management through the batch
submission of a server-side workflow engine (Moteur ). 

Applications running on a Grid can be exposed by EnginFrame as WSDL/SOAP standards
Web Services and made available, inside a service-oriented architecture, to consumer
applications. 
Furthermore EnginFrame technology hides the complexity of the underlying Grid
infrastructure and provides an additional user-oriented abstraction layer on the Grid.

The most important goal is the introduction of a server-side component for the
execution of workflows on a Grid infrastructure away from user workstation. This
provides advantages from both user’s and administrator’s point of view.
Users don’t have to install any software tools and worry about software upgrade and
maintenance but simply run and monitor their own workflows from everywhere using a
standard Web browser. On the other hand, administrators have a full control of
workflow access and submissions.
Moreover, thanks to multi-platform architecture, this solution can greatly simplify
the development.

Diligent is an ongoing IST project that aims to combine Grid and Digital Library (DL)
technologies in order to provide an advanced test-bed DL infrastructure allowing
members of dynamic virtual e-Science organizations to access shared knowledge and to
collaborate in a secure, coordinated, dynamic and cost-effective way. 
In particular, Diligent builds on top of the Enabling Grid for E-sciencE (EGEE)
project which is providing the one of the largest European Grid Infrastructure and
the support to the gLite Grid middleware. 
From an abstract point of view, the Diligent infrastructure acts as a DL broker,
where the clients of the broker are DL resource providers and consumers. The
providers are the individuals and the organisations that decide to make available,
under the supervision of the infrastructure, their resources according to certain
access and use policies. The consumers are the user communities that want to build
their own DLs. The resources managed by this broker are of different types:
collections (i.e., set of information objects searchable and accessible through a
single “access point”), services (i.e., software tools implementing a specific
functionality and whose descriptions, interfaces and bindings are defined and
publicly available), hosting nodes (i.e., networked entities that offer computing and
storage capabilities and supply an environment for hosting collections and services),
and EGEE resources (i.e., computing elements and storage elements).
In order to support the controlled sharing of resources among providers and
consumers, the Diligent infrastructure relies on the virtual organizations (VOs)
mechanism that has been introduced in the Grid research area. This mechanism models
set of users and resources aggregated together by highly controlled sharing rules,
usually based on an authentication framework. 
By exploiting appropriate mechanisms provided by the infrastructure, providers
register their Diligent resources by supplying a description of them. According to
the type of resources provided, the infrastructure also automatically extracts other
properties that are used to enrich the explicit description. The infrastructure takes
care of the management of the registered resources by supporting their discovery,
monitoring, reservation, and by implementing the functionality needed to support the
required controlled sharing and quality of service. 
A user community can create one or more DLs by specifying a set of requirements and
by appropriately combining the available resources. These requirements specify
conditions on the information space (e.g., the set of collections, subject of the
content, documents type), on the services for supporting the work of the users (e.g.,
type of search), on the quality of service (e.g., availability, performance,
security) and on many other aspects, like the maximum cost, lifetime, etc. The DL
broker satisfies the given requirements by selecting, and in many cases also
deploying, a number of resources among those accessible to the community, gluing them
appropriately and, finally, making the new DL application accessible through a portal.
The composition of a DL is dynamic since the infrastructure continuously monitors the
status of the DL resources and, if necessary, changes them in order to offer the best
quality of service. Therefore, DLs (possibly serving different communities) can be
created and modified on-the-fly, without considerable investments and changes in the
organisations that set them up.

The potential of the Diligent infrastructure is being demonstrated and validated over
two complementary real-life application scenarios deriving from the environmental
e-Science, named ImpECt, and the cultural heritage, named ARTE, domains. 
ImpECt (Implementation of Environmental Conventions) includes leading actors in the
environmental sector, and is represented by the European Space Agency (ESA). This
community exploits the DILIGENT to support conference organisation and the
preparation of projects and periodical reports. International and regional
conventions related to earth observation represent the framework for formulating
international environmental agreements. These conventions are continuously evolving
and thematic areas are specialising. Yet, information sources are dispersed among
environmental agencies and a DILIGENT-based DL could be the most appropriate tool to
enable this community to more effectively coordinate actions.
ARTE is a community of scholars located all over the world, working together to
establish a new discipline that merges experiences from research in humanities,
social sciences and communication. In order to achieve their objectives these
researchers require a common background knowledge base. The DILIGENT platform
provides them, in a short time framework, a cost-effective instrument for setting up
DLs, i.e. common multimedia knowledge repositories equipped with a number of
services, specifically tailored to the needs of this community. The ARTE community is
represented in DILIGENT by the Scuola Normale Superiore (SNS), one of the partners
contributing rich archives of texts and images. Audio-video content is being provided
by the Italian National Broadcasting RAI Educational.

The Diligent project is currently testing the first prototype that will be delivered
by the end of September ’06. 
According to the Diligent implementation plan, this version is not fully-fledged.
Rather it supports the basic DL functionalities required to satisfy the main user
communities’ requirements. All the DL functionalities: (i) have been designed in
accordance with the Service Oriented Architecture paradigm, (ii) have been
implemented as WSRF compliant service elements, and (iii) are powered by the EGEE
gLite middleware components. 
In particular, this prototype provides:
•	On-demand services deployment on nodes equipped with the Diligent VO box;
•	Content security handling (access and watermarking policies);
•	Semantic content management over a gLite superimposed storage management layer;
•	Metadata management and indexing;
•	Annotation management and visualisation;
•	Complex process visual design, verification, optimisation and execution;
•	Text, image, sound, video and multimedia content processing;
•	Information visualisation;
•	Information retrieval out of structured, semi-structured and unstructured data;
•	Support for application-specific extensions.

In addition to the above functionalities, application specific ones have been
integrated to better support the two user communities.
The aim of this talk is to present the Diligent prototype. In particular, the talk
focuses on a specific functionality, relevant to the ARTE community, dealing with the
management of copyrighted videos on the gLite based Grid infrastructure. It has been
implemented exploiting the process visual design, verification, and optimisation
capabilities to combine content and metadata management, content security handling,
and indexing. The so designed workflow allows to import, secure, and make available
generic set of videos originally stored in a storage device. This complex workflow
has been executed on the Diligent sites belonging to the EGEE PPS infrastructure and
a set of statistics have been collected.

Presnetation of CESNET activities in JRA1

Description of SA3 activities of PSNC

1 presentation by each country involved
2-3 minutes per presentation

1 presentation per each contry involved
5 minutes each

The simplification of the access to powerful Grid 
infrastructures with the help of an
integrated Grid workbench tool is the goal of the g-
Eclipse project. The project
started on July 1, 2006 and is partially funded by the 
European Commission. The
integrated Grid environment will address all needs of 
possible Grid activities and
Grid actors. The current lack of an uniform Grid 
workbench toolbox, which will be an
entry point to the Grid resources, will be removed with 
the g-Eclipse framework. The
project plans to deliver the future workbench, bringing 
together new users,
applications and Grid resource providers. The main goal 
for g-Eclipse project is to
prepare integrated Grid environment for all grid 
activities. The idea is, that the
same toolbox can be use for utilizing grids in 
applications, for operating and
managing the grid infrastructure, and for developing 
grid applications. g-Eclipse
will be based on Eclipse, probably the most successful 
IDEs nowadays. Eclipse was
developed by IBM in 2001 and then turned to the 
nonprofit Eclipse Foundation
(www.eclipse.org), to be managed as an open-source 
platform.The architecture of the
g-Eclipse framework will be made for reuse and 
extension to allow for easy adaptation
by new Grid applications. The g-Eclipse project will 
address three major groups in
the Grid domain: Grid users will benefit from the 
Windows-like access to Grid
resources; Grid operators and resource providers will be 
able to reduce the
time-to-service by the Grid management and Grid site 
configuration tools; and Grid
application developers will reduce the time-to-market 
for new Grid applications by
accelerating the development and deployment cycle. 
The g-Eclipse project aims for general support for 
different Gird middleware systems,
but in the first year the g-Eclipse framework will include 
exemplary support for the
gLite middleware. 
The project itself, the main ideas and the requirements 
to an EGEE infrastructure
will be presented. First integrated tools as prototypes 
will be presented. The poster
should help to get in touch with potential users of the 
framework, the gLite
middleware developers as well as with other 
applications developers.

The presentation (poster) aims to introduce Special 
Interest
Group (SIG) concept,
being developed as an application in BalticGrid project
(www.balticgrid.org). SIG is
going to be implemented as a public service based on 
grid
technology.
The main task of SIG is to enable group-to-group
communication of scientists and
researchers, having similar or related R&D interests (to
create virtual spaces). The
functionality of SIG is based on grid computing
infrastructure, introducing new
possibilities and features to a virtual space. Beside
teleconferencing, which is most
standard function in such case, other functions may be
offered: application-
(computing-), resource-, data-, file-, desktop sharing, 
some
others. The software for
SIG is based on AccessGrid open source software, with 
many
modifications, adds,
additional components for the BalticGrid environment. 
As a
collaboration tool SIG
provides participant information, data storage, BalticGrid
services, application
sessions. Research areas under consideration for SIG 
to be
developed and implemented
are: Baltic Sea Eco-System Modelling; Text Annotation
Service; Text-to-Speech
Service; Stellar Spectra Computation; Atomic and 
Nuclear
Computations; Computational
Modelling of heterogeneous Processes.

JKU/RISC currently develops in cooperation with Upper
Austrian Research (UAR) the
SEE-GRID software system. SEE-GRID is based on the SEE++
software for the
biomechanical 3D simulation of the human eye and  its
muscles. SEE++ simulates the
common eye muscle surgery techniques in a graphic
interactive way that is familiar to
an experienced surgeon. SEE++ is world-wide the most
advanced software for this
purpose; it is used by various hospitals and medical doctors
for surgery training and
planning,

SEE++ deals with the support of diagnosis and treatment of 
strabismus, which is the
common name given to usually persistent or regularly
occuring misalignment of the
eyes. Strabismus is a visual defect in which eyes point in
different directions. A
person suffering from it may see double images due to
misaligned eyes. SEE++ is able
to simulate the result of the Hess-Lancaster test,  from
which the pathological
reason of strabismus can be estimated. The outcome of such
an examination is two gaze
patterns of blue points and of red points respectively. The
blue points represent the
image seen by one eye and the red pointsthe image seen by
the simulated other eye,
but in a pathological situation there is a deviation between
the blue and the red points.

In SEE++, a third gaze pattern, a measured one (with green
points) of a patient can
be given as  input. In this case, SEE++ takes some default
or estimated eye data and
modifies a subset of them until the calculated gaze pattern
of the simulated eye (red
points) matches the  measured gaze pattern. This procedure
is called pathology
fitting.  The current algorithm is time consuming and gives
only a more or less
precise estimation for the pathology of the patient. Doctors
want to see quickly the
results from such a decision support system, but for
reaching adequate response times
it is not sufficient to use only local computational power.

The goal of SEE-GRID is to adapt and to extend SEE++ in
several steps and to develop
an efficient grid-based tool for Evidence Based Medicine,
which supports the surgeons
to choose the best surgery techniques in case of the
treatments of different
syndromes of strabismus. We approach this goal in three phases:

- We have implemented a parallel and grid-enabled version of
the Hess-Lancaster test
simulation (it is based on the Globus Toolkit at present).

- We are currently developing a grid-based medical database
described for storing and
sorting patient data with gaze patterns and eye data.

- We plan to make a gLite compatible version of SEE-GRID and
then further develop it
on the basis of the higher services of the EGEE-II
middleware (comparedwith the
low-level services of the Globus Toolkit).

- We will work on a parallel grid-enabled pathology fitter
algorithm.

References:

1. Károly Bósa, Wolfgang Schreiner, Michael Buchberger,
Thomas Kaltofen, SEE-GRID, A
Grid-Based Medical Decision Support System for Eye Muscle
Surgery. 1st Austrian Grid
Symposium, December 1-2, 2005, Hagenberg, Austria. OCG
Verlag, 14 pages.
http://www.risc.uni-linz.ac.at/people/kbosa/papers/1st_AGRID_Symp_Proceedings2006.pdf

2. SEE-GRID Technical report page:
http://www.risc.uni-linz.ac.at/research/parallel/projects/agrid/results/

The variety of EGEE applications come up with many different
requirements. For
example, biomedical and generic virtual organizations (VOs)
run jobs for five
minutes, whereas high energy physics (HEP) jobs can run for
days. Some mechanisms
have been investigated to make this cohabitation
satisfactory in leveraging theories
from economics. Additionally, thanks to virtualization, it
is now possible to make
the allocation as dynamic as electric power supplies, and to
implement schemes that
lead to an optimal resource utility. Such a system has been
implemented in HP Labs
and tested in CERN openlab. An interesting approach in the
future would be to have
our grid infrastructure benefit from it without losing the
capabilities of current
allocation architecture and strategies, like static
contracts between VOs and
service-level agreements. If successful, such an integration
could also be an early
step towards organizing grid self-sustainability.

A computational grid is a hardware and software
infrastructure capable of 
providing dependable, consistent, pervasive, and inexpensive
access to high-
end computational resource. There are many ways to access
the resources of a 
computational grid, each with unique security requirements
and implications for 
both the resource user and the resource provider. Current
Grid security 
Infrastructure using PKI based on SSO. But open grid service
Security 
Infrastructure in Global Grid Forum (GGF) will extend use of
grid system or 
services up to business area using XML web services security
technology. This 
paper describes a novel security approach on open grid
service to validate 
certificate based on current globus toolkit environment
using XKMS(XML Key  
Management Specification) and SAML(Security Assertion Markup
Language), 
XACML(extensible Access Control Markup Language) in XML
security.

The increasing availability of computer power on distributed
platforms
makes it easier to perform molecular based simulations of
complex systems
in order to reproduce their macroscopic properties. In this
report we outline
the work carried out in our laboratory by performing a
molecular dynamics
simulation of the Propane bulk system in liquid and gas phase. 
The calculations were aimed at estimating in an a priori
fashion some thermodynamics
properties of the system and to build the related phase
diagram [1]. To
this end the DL_POLY [2] software package was used for the
npt statistical
ensamble at different temperatures. Computational tasks were
distributed
using the EGEE-Grid platform [3].
    To obtain preliminary indications on the performance of
the used platform,
 a test case was run on six different EGEE-Grid clusters. In
order to
evaluate the elapsed time of each simulation and the related
speed-up for
each cluster, we ran the calculations sequentially on one
node and in parallel 
on 2 and 4 nodes. Measured elapsed times and speedups will be 
illustrated at the meeting. The parallel performance of some
clusters of the 
EGEE-Grid is very close to the ideal value due to
their dedicated usage. Deviations from it occurring in the
other clusters are
mainly due to the time sharing regime adopted by them. This
means that
the parallel performances of each EGEE-Grid cluster strictly
depend on the
adopted regime. In order to evaluate more in detail the
parallel performance
of each cluser and the waiting time intercurring between the
scheduling and
the running of a process we restricted parallel calculations
to two nodes. To
carry out a statistical analysis we ran 50 parallel jobs. As
apparent from the table, 
more than 70% of the jobs ran properly and only 26% was
aborted. 
Abortion is due for 62% to comunications errors between the
nodes of the same cluster, for 23% to internal errors of DL
POLY occurred
during the running and for 15% to the scheduler.
    The calculated value of the density of the system gets
closer to the data
given in literature (582 Kg m(E-3) at T=230 K at P=1.013 bar
[4]) when
going from 200 K to 230 K. At the same time we computed
high values of pressure and correlated statistical errors.
Possible ways out
of this problem can be an increase of the simulation time in
order to obtain
a better average value of the pressure and/or a small
modification of the
force field of the system in order to normalize the effect
of the pressure on
the system.

References
[1] Costantini, A., Lagana', A., Pirani, F.: Lecture Notes
in Computer Sci-
   ence 3980 (2006) 738-713.
[2] Smith, W., Forester, T.R.: DL POLY2: a general-purpose
parallel
   molecular dynamics simulation package. J. Mol. Graph. 14
(3) (1996)
   136-141
[3] Storchi, L., Manuali, C., Gervasi, O., Vitillaro, G.,
Lagan, A., Tarantelli,
   F.: Lecture Notes in Computer Science 2658 (2003) 297-306.
[4] Air liquid group website: http://www.airliquide.com

the eIMRT project  is currently carried out by diverse
institutions in Galicia 
(Spain) and the USA. The eIMRT project will make available a
set of algorithms 
to optimize and validate radiotherapy treatments to the
radiotherapists, both 
CRT- and IMRT-based, hiding the complexity of the computer
infrastructure 
needed to solve the problem using GRID technologies. The new
platform is 
designed to be independent of the medical accelerator
models, scalable and 
open. Having a web portal as client, it is designed in three
layers using web 
services which will allow users to access it directly from
any kind of front-ends 
and clients. It has three main components, namely remote
characterization of 
linear accelerators for Monte Carlo and
convolution/superposition (C/S) dose-
calculation techniques, remote Grid-enabled radiotherapy
treatment planning 
optimization and verification and data depository.

In BME we have assembled a site consisting of a Grid Gate
(GG), a Storage Element
(SE) and over thirty Working Nodes (WN). The GG and SE as
well as many of the WNs are
HP ProLiant G2 servers with two Intel Xeon 3.00GHz
processors and 2GB RAM.

In most cases it is very difficult to maintain and
administer such sites. Expanding
these with new nodes is a time-consuming task that requires
extraordinary attendance.
We have created an NFS based solution, which allows nodes to
be added in a matter of
minutes without prior installation of gLite software. The
worker nodes are nearly
diskless: most part of the file system on each is served via
NFS root located on the
GG host. This supplies all the necessary applications and
configuration files to
operate in the Grid environment. Only temporary data files
and the host-specific
private keys and certificates are stored locally. The latter
two are required by the
PKI based authentication mechanism that is commonly used in
Grids such as the EGEE
Grid. It is also possible to deploy completely diskless
nodes where these are
downloaded from a secure network. The hosts may contain
large capacity disks, which
can be used not only for temporary storage for the worker
nodes, but as a storage
disk in a Disk Pool Manager (DPM) architecture. The
operating system is still served
by NFS or another possibility is to download a complete file
system image to a local
hard disk. With this realization we have created an easily
manageable site.

The hosts are connected with a Gigabit Ethernet network,
which also connects them to
an HP Scalable File Share (SFS) storage system of
approximately 3 Terabytes capacity.
To make both the GG and SE accessible from outside, each of
them has another network
interface which connects it to the Internet. The site is
part of the EGEE
infrastructure, and hence runs the gLite middleware. We have
also established a
Virtual Organization called “egeebme” and a local
Certificate Authority for testing
and educational purpose. This allows students and
researchers to become acquainted
with gLite without applying for a globally accepted
certificate and VO membership.

The homogeneous set of the HP servers makes it possible to
use one common kernel
image on each host without further configuration on the
hosts separately. Inserting
another identical HP ProLiant G2 server needs no special
action. For other hardware
configurations, only a different type of kernel image is
required, but the same NFS
root can be used. User authentication on the site is
provided by Kerberos and LDAP
running on the GG machine. The system on the SE contains the
client tools for the HP
SFS and is configured to make the storage space available to
the Grid infrastructure.
 
The SFS is based on the Lustre File System, and provides an
efficient administration
environment and a single point of management. The flexible
Lustre technology permits
a huge variety of configurations. Meta-data and object data
is stored on different
disks, providing separate scalability for both. This allows
grid administrators to
fine tune the system to meet the specific needs of the
different types of
applications. Files are stored on Object Storage Targets
(OST) and administrative
data is handled by the meta-data Server (MDS). File-data can
be striped across
multiple OSTs; allowing extreme file sizes and multiplying
file I/O performance. 

SFS provides a network-independent solution with high
network performance,
redundancy, higher availability and transaction rates than
the standard solutions,
also offering compatibility between different types of
distributions and
architectures. It can be reached through the conventional
standard network file
systems. Network bandwidth and latency is improving rapidly,
which obsoletes current
storage technologies. HP SFS therefore supports the most
recent types of network
systems as interconnect. Gigabit Ethernet is only the
slowest possibility, but
InfiniBand or Myrinet can provide  770 Mbyte/s network
performance.

Robust computing nodes require an effective and reliable
access to the main file
system. While using NFS, we have been experiencing file I/O
malfunctions, so we have
been looking for a more sophisticated solution. By upgrading
from NFS to SFS based
centralized file systems random failures and network
dropouts can be eliminated.

In addition to being part of the European Grid, the site
serves as a computing
cluster for the computations at BME Faculty of Architecture.
The problem being solved
is calculating the prestressing strength of reinforced
concrete bars used in bridges.
This can be modeled as a Boundary Value Problem (BVP) that
is easy to parallelize by
parameter sweeping, i.e. dividing the parameter domain into
smaller subdomains each
node can work on separately.

The main goal of the project is to extend gLite to Microsoft
Compute Cluster Server
(CCS) platform, with the first phase to make CCS as the work
node of gLite
infrastructure.. Heterogeneity is the beauty of Grid, but
still a milestone to reach.
To integrate the large population of Windows-based resources
into the Grid world
through Grid services is also essential to acquire more
momentum from the industry
and from the grass-roots. In general, we successfully make
CCS nodes running jobs
from gLite resource broker and Windows jobs are able to
execute natively under the
control of  gLite as well. 

The main challenges of this project stem from the essence of
 Unix and Windows. For
example, gLIte makes use of plenty of shell scripts for
wrapping end users’ job
descriptions to meet the target environment and get
dispatched and executed on the
fly, but we are short of such flexible tools in Windows. Job
profiles have to be
re-compiled for Windows. For the bridge of gLite and CCS, we
take advantage of gLite
CE’s BLAHP interface, an abstract layer for underlying
queuing systems.A set of API
and tools were developed upon BLAHP to let jobs submitted
from each side. . Job
submission approach is persistent as the gLite way entirely.
To demonstrate the
effectiveness of our works, BLAST and virtual screening
applications were ported and
tested with success. In the future, we plan to have the
proxy delegation to Windows
nodes, GSI-based data transmission in Windows, and the fully
compatible storage
element could be developed in the next phase.

Intensive Care Units (ICUs) at hospitals utilize cutting
edge technology in order 
to acquire the physiological state of inpatients at an
extremely high fidelity. 
Such measurements can then be utilized for i) education, ii)
early diagnosis and 
iii) for defining early warning systems that identify when a
human life is 
jeopardy. A problem with the current setting is that
individual ICUs are limited 
to the locally acquired measurements. As a result, the
number of 
clinically "interesting" episodes available to doctors is
also very limited.  

The ICGrid (Intensive Care Grid), is a platform that will
enable the seamless 
integration the physiological parameters acquired at ICUs
scattered around 
Europe. Such a task requires huge processing and data
storage capabilities, 
which are common attributes of the EGEE GRID infrastructure.
ICGrid is based 
on a hybrid architecture that combines i) a heterogenous set
of monitors that 
sense the in-patients and ii) EGEE GRID technology that
enables the storage, 
processing and information sharing task between Intensive
Care Units.

The project’s goal is to introduce an easy and versatile way
to provide and use Grid
resources, acting both as a Worker Node and User Interface,
without the need of any
operating system installation or middleware configuration on
users' machines. 
At the same time it provides an excellent training tool for
new Grid users and
novices that want to experiment, without requiring
installation. It has been tested
thoroughly under different circumstances with success.
LiveWN works in the form of a
LiveCD or memory stick under a virtual machine within many
popular host operating
systems.

With Grid technologies and software agents becoming
increasingly relevant in the
sphere of distributed systems, it is suggested by many that
these two technologies,
far from being contradictory, serve an important
complementary function. Grid
technologies focus on a robust and extensible
infrastructure. Agent systems
concentrate on autonomous and flexible behaviours. Both
would benefit from utilising
the relative strengths of the other. Motivated by this
desire, we review the current
state of the art of both areas, review the challenges that
both communities face and
examine current attempts to develop an integrated strategy
that promises an enhanced
symbiosis between the two approaches. We propose an approach
to a unified Grid/agent
framework that has the ability to support the development of
distributed systems that
would, at the same time, be robust, extensible, autonomous
and flexible.

Errors are always frustrating. They are even more
frustrating when their cause is not
clear. And the GRID is not an exception. For example,
submitting a job to the GRID
and getting back an error is frustrating. Not knowing if the
error was due to
something you did, some middleware glitch or a site problem
makes it even worse. 

Our goal was to tackle this problem. In order to do that,
the first thing is to
understand the different error messages reported back to the
users. We went through
the most common error messages: first, investigating the
underlying problems; then
categorizing, and if possible, helping the responsible to
fix it; and finally
monitoring if that error message disappeared. 

One common reason for job failures is site misconfiguration.
Being able to detect
such a misconfiguration as soon as possible helps in several
ways: first of all, it
minimizes the time that it takes to bring the site back to a
normal state; moreover,
debugging it is easier, since the problem happened in the
recent past.

In the next chapters we will describe in more detail the
study that we did for some
of the error messages. We will also describe the tools that
we created to monitor the
site efficiency.

Over the last few years, Grid Computing has adapted to Web
Services 
standards with the emergence of Web Services Resource
Framework (WSRF). 
This alignment with Web Services standards has made the Grid
standards more 
scalable by enabling Grid resources interoperable over the
Web. The next step 
for Grid is Semantic Grid in which knowledge about resources
is exposed and 
handled explicitly.

It is envisioned as semantic layering over the current Grid
infrastructure. 
Semantic Web Services technologies can be applied to the
Grid in a way to 
achieve the Semantic Grid vision. For example, the
background knowledge and 
vocabulary of a Grid middleware component could be captured
in ontologies. 
Metadata can be used to label Grid resources and entities
with concepts, for 
example describing a data file in terms of the application
domain where it is 
used. Rules and classification-based reasoning mechanisms
could be used to 
generate new metadata from existing metadata, for example
describing the 
rules for membership of a VO and reasoning that a potential
member’s 
credentials are satisfactory.

Moreover, activities like Grid service discovery or
negotiation of service level 
agreements, among others, can be potentially enhanced using the 
functionalities provided by Semantic Web Service technologies.

Started far apart in applications and technology, grid
services and web services 
converged (Grid services started with GT1, web services
started with XML, 
SOAP and WSDL, and finally converged as WSRF, an extension
of web services 
that considers grid specific requirements), but still they
are defined at a 
syntactical level, without any formal
semantic that would make the suitable for automation. A
technology is needed 
that will extend and enrich these service descriptions with
new elements that 
will allow to automatize service related tasks. The
conceptual model of WSMO, 
and WSML, the formal language that reflects the conceptual
model, will allow 
different types of automatic proofs to be made in this
language, thus providing 
a certain level of automation for service related tasks.

The OGSA framework, the conceptual model for grids, defines
different types of 
services with specific capabilities that are needed for grid
applications. 
However, OGSA doesn’t provide a formal language for
describing these 
services, thus being of little use in automatic performance
of different service 
related tasks. Current languages used in
grid, like GRAM (grid resource allocation manager), are
based on XML and XML-
schema, thus inheriting all its drawbacks (semi structured
data format, no 
formal semantics, no reasoning support, etc); here is where
OGSA could benefit 
from the conceptual model of WSMO and its associated
language, WSML.

All the OGSA services, which are summarized below could
employ WSMO for 
semantically describing their properties: Infrastructure
Services - OGSA 
leverages Web services architecture to implement a SOA. WSDL
is used for 
service descriptions. SOAP is the communication protocol.
Here WSMO/WSMX 
will be helpful. Initially this infrastructure was based on
OGSI but now it will be 
based on WSRF.

WSMO conceptual model can be extended to cope up with
complexity of Grid 
Services. The extended WSMO model for Grid can act as
specification to realize 
Semantic Grid
Services.

Execution Management Services - These services deal with the
problems of 
task initiation and management. Grid resource broker uses
the status 
information for each resource stored in monitoring and
discovery service to 
discover a resource and initiate a job or set of jobs on
that resource. After 
scheduling jobs, it also gathers information on the status
of jobs. With the 
emergence of Semantic Grid, the information stored by Grid
resource broker has 
to be made semantically annotated which will enable the Semantic
Grid infrastructure to manage, monitor and discover the
available grid 
resources automatically, more easily and more precisely.

Data Services - Data services in the grid are responsible
for efficient data 
access, data consistency, data persistency, data integration
and data location 
management.
Triple Space Computing associated closely with Semantic Web
Services can 
bring next level of advancement in the Data services of gird. 

Resource Management Services - These services allow the
management of 
individual resource itself, management of resources in Grid
(i.e. resource 
reservation, monitoring
and control) and monitoring of Grid infrastructure which
consists of resources 
as well like monitoring the registry service. Semantic
annotations to grid 
services will improve the Resource Management by providing
explicit meta-
information to describe the resources of Grid.

Security Services - Security services provide controlled
access to resources 
which can be in various administrative domains with
different access and 
security policies. Grid Security Infrastructure (GSI)
specifies the whole set of 
protocols and security architectures that are required for
controlled resource 
sharing across the Grid. Semantic annotations to Grid
resources and other 
entities will also help the security services to have a
clear and unambiguous 
scenario and to act accordingly for authentication and
authorization of the 
resources.

Self-Management Services - Self-management services include
SLA, policies and 
service level manager model. SLA includes business and IT
agreements 
between the provider and user of the service. Policies are
used to govern the 
behavior of an SLM (Service Level Manager) and the
manageable resources 
under its control. Service Level Manager Model provides the
interface such that 
various human operators and SLM can work together without
having 
knowledge about each other built in at design time. Service
level agreements 
(SLAs) are currently being investigated by Semantic Web
Services community as 
well. However, explicit availability of meta information
will enable the self 
management of services more automatic and dynamic.

Information Services - Monitoring and Discovery Service in
OGSA is an XML 
database called Xindice that collects information from each
of the resource in 
Grid. It Stores dynamic data for monitoring and discovery.
It also acts a registry 
for grid services. XPath and XQuery languages are used to
query data from 
information service. Semantic annotations to the
intermediate information of 
Grid will make the monitoring and discovery in Grid more
precise and accurate in 
complex and dynamic scenarios.

Acknowledgements
The work is funded by the FIT-IT (Forschung, Innovation,
Technologie - 
Informationstechnologie) under project GRISINO - Grid
semantics and intelligent 
objects. The authors would like to thank all the people who
are involved in 
GRISINO project and the funding support from Austrian
Government.

Detecting and managing failures in an automated way is an
important step 
toward the goal of a dependable grid. Currently, this is an
extremely complex 
task that relies on over-provisioning of resources, ad-hoc
monitoring and user 
intervention.  We present the FailRank architecture, a
simple yet powerful 
framework for integrating and ranking information sources
that characterize 
failures in a grid system. In the FailRank architecture,
feedback sources (e.g. 
websites, LDAP queries, representative low-level
measurements, etc) are 
continuously coalesced into a representative array of
numeric vectors, the 
FailShot Matrix (FSM).  FSM is then continuously ranked
using efficient top-k 
query processing algorithms in order to identify the K sites
with the highest 
potential to feature some failure. This allows system
administrators to focus 
their attention on the sites with the highest potential to
run into failures and 
resource brokers to divert jobs away from the respective
sites. We identify 
challenges and preliminary solutions for a variety of
complementary tasks 
including exploratory data analysis and prediction.

XtremWeb-CH (www.xtremwebch.net) is an applied research
project carried out at the 
University of Applied Sciences, Western Switzerland.
XtremWeb-CH aims at building an 
effective Peer-To-Peer Large Scale Distributed System for
high performance needs. A 
typical XtremWeb-CH platform is composed of one coordinator
and several workers 
(remote resources). The coordinator is a three-tier layer
allowing “connection” between 
the users of high performance applications and the workers.
XtremWeb-CH supports four functionalities:
1.	Volatility of workers: When a worker voluntarily or
involuntarily disappears, the 
task allocated to it is automatically assigned to another
worker.
2.	Automatic execution of Parallel and Distributed
Applications: a high 
performance application is generally composed of a set of
communicating tasks. 
XtremWeb-CH insures the automatic transfer of data between
workers executing 
communicating tasks.
3.	Direct communication between workers: Communication
between tasks can 
take place without passing through the coordinator. The
coordinator keeps only the 
responsibility of assigning tasks to workers.
4.	Load balancing: XtremWeb-CH optimizes the granularity of
the application 
according to the “state” of the platform. During the
“compilation” step, the number of 
tasks and the workload (quantity of data to be processed) of
each task are fixed 
according to the number of the available workers and their
performance. During 
execution, a scheduling algorithm assigns tasks to workers
according to the workload of 
the former and the performance of the latter.
XtremWeb-CH provides a set of monitoring tools allowing
users to visualize the execution 
of their applications: tasks allocation, execution
progression, step by step execution, etc.
XtremWeb-CH is evaluated in a real case of a CPU time
consuming application, PHYLogeny 
Inference Package: PHYLIP
(http://evolution.genetics.washington.edu/phylip.html).
The parallelized version of PHYLIP is used by the virology
laboratory of Geneva Hospital in 
order to generate phylogenetic tree related to HIV virus.

We monitor resources for VO VOCE by bunches of very short jobs 
sent to all computing elements supporting VOCE available in
the time
of test. Some sites reserve special nodes or queues for
standard Site
Functional Tests, in our approach we get the same response
as a normal 
user without privileges. We obtain not only binary result
passed/failed, 
but a percentage of jobs finished successfully. From these
tests we 
can conclude that some resources are able to run short
analysis jobs. 
Additional statistics about performance of VOCE Resource
Brokers is 
collected.

Auger collaboration (www.auger.org) builds a huge detector
for a 
measurement of ultra high energy cosmic rays. EGEE grid
tools are 
evaluated if they are suitable for a data distribution and a
running
of Monte Carlo simulations. We prepared infrastructure for
the new 
VO and we added first computing resources. A status of a simple 
user friendly framework for CORSIKA simulation jobs will be
presented.
We expect that this poster will help to add new resources to
the 
AUGER.ORG VO.

MediGRID - Medical Grid Computing 

Sax U1, Viezens F1, Mohammed Y1, Lingner Th2, Morgenstern
B2, Vossberg M3, 
Krefting, D3, Rienhoff O1

1Department of Medical Informatics, University of Göttingen,
Germany
2Department of Bioinformatics, University of Göttingen, Germany
3Department of Medical Informatics, Charité, Humboldt
University Berlin, 
Germany
fred.viezens@med.uni-goettingen.de

Introduction
The project MediGRID [1] combines research institutes from
various areas of 
Medicine, Biomedical Informatics, and other Life Sciences.
Numerous associated 
partners from industry, healthcare and scientific
institutions ensure a broad 
representation of this large community. The main goal of
MediGRID is the 
development of a grid-middleware-platform with Globus
Toolkit 4 as a basis for 
eScience Services for the community and to help researchers
to use these 
services. Here we present the first results of the projects
consisting of the 
infrastructure, first community applications and basic
privacy rules.

Materials and Methods
Concerning the data flow in grids, most projects are similar
in the lower layers 
(s. Fig. 1), but the biomedical community has to face
particular challenges in the 
upper layers. The top layer represents the heterogeneous
biomedical data 
sources. Beyond the problem to find the relevant data sets
via metadata 
description, access control to the data is of paramount
importance, as the 
owner of the data are foremost the patients. Due to the
heterogeneity of the 
data we need an additional ontology layer to homogenize the
data. Given 
semantic interoperability the researcher can correlate and
analyze the data 
with biomedical informatics methods. Biomedical data in
medical grids are 
heterogeneous, contain different kinds of information and
have different levels 
of privacy. The data might include information about [2]: 

•	 Population: Epidemiology 
•	 Diseases: Clinical practice, clinical trials
•	 Patient data: Health record, clinical history, physical
exams, 
lab/imaging studies
•	 Organ/tissue: pathology
•	 Cellular: histology
•	 Molecular: genetic test results and genomic data.
Having these data online with the suitable tools to connect,
combine and 
analyze creates new challenges for data protection and privacy.

Results 
The current privacy concepts do not cover the aspects and
abilities of grid 
computing. Especially the re-identification risk with the
combination of different 
data types has to be assessed.  There are severe privacy
concerns related to 
genomic-wide association studies [3-5]. These are the main
reasons for the 
development of an enhanced security concept for MediGRID. Four 
methodological modules are responsible to construct the
suitable 
infrastructure: ontology, resource fusion, middleware and
eScience. On the 
other hand, three research modules take the initiative to
use this national grid 
infrastructure to assist their work: biomedical Informatics,
image processing 
and clinical research. The MediGRID consortium developed a
middleware 
component as a connector for the medical community to
resources of the 
integration project in D-Grid [6]. 
The community modules use this middleware to “gridify” their
applications in 
order to show the advantage of grid computing in medicine. 

Ontology
Using OGSA-DAI as a standard of Data Access and Integration
in grids, the 
ontology module has successfully developed an ontology tool
and implemented 
it as a first step to be a Gridsphere-Portlet in the
MediGRID portal being 
available for all project partners.

Bioinformatics
Dialign is a widely used software tool for multiple
alignments of nucleic acid and 
protein sequences. Within the MediGRID portal a parallelized
version of the 
software is used to speed up the computationally expensive
procedure. In that 
way distributed computing allows the user to obtain
high-quality alignments of 
bigger databases and longer sequences. AUGUSTUS is a program
that predicts 
gene structures in eukaryotic genomic sequences with high
accuracy. Since 
AUGUSTUS performs a successive analysis of overlapping
sequence sections, it 
is easy to parallelize. Therefore users benefit from
distributed computing with 
several instances of the program. Grid resources also allow
frequent update 
and centralized storage of huge EST databases.

Image Processing
A 3D image reconstruction for prostate biopsy will register
the different 
ultrasonic scans helping the physician to have a new viewing
of the prostate 
that was not possible using the traditional 2D methods. The
virtual vascular 
surgery helps to calculate and present the animated 3D blood
flow field in the 
brain vessels, which could be used to anticipate the
pressure on the walls of 
the vessels and for example to predict a bleeding risk. The
Brain 4D MRI image 
processing application in MediGRID assists the
identification of the brain areas 
research. All three applications are demanding the
possibility of massive data 
volume storage and processing. Because of the constant
increase of the data 
volume coherent with the development in the imaging
techniques, a dynamic 
extendable computing and storage infrastructure is needed,
which ideally will 
be a grid environment.

Privacy
In the first step we are working with non person-related
data and set up the 
first generation of privacy rules. As a preparation for the
next phase – dealing 
with person related data – we defined the additionally
necessary advanced 
security methods like audit and tracking. Furthermore some
legal issues 
concerning virtual organizations and the ownership of data
and material have 
to be addressed.

Further perspective 
As we gained experience with our first medical grid
applications, we will be able 
to “gridify” other community applications more easily. The
initial incarnation of 
the infrastructure is set up; some details are still to
come. As genotyping 
constantly gets cheaper, many formerly phenome-related
projects around 
complex diseases consider genotyping within the next couple
of years. Beyond 
the indisputable opportunities of these studies there are
quite some challenges 
to be faced.  MediGRID addresses issues like the
homogenization of 
heterogeneous data sources and how do we deal with the
well-known privacy 
problems. Solving those issues will enhance the portability
of life science grid 
services to other projects and other communities. 

References
1 www.medigrid.de
2 Martin-Sanchez, F., V. Maojo, and G. Lopez-Campos,
Integrating genomics 
into health information systems. Methods Inf Med, 2002.
41(1): p. 25-30.
3 Butte, A.J. and I.S. Kohane, Creation and implications of
a phenome-genome 
network. Nat Biotechnol, 2006. 24(1): p. 55-62. 
4 Lin, Z., A.B. Owen, and R.B. Altman, Genetics. Genomic
research and human 
subject privacy. Science, 2004. 305(5681): p. 183. 
5 Kohane, I.S. and Altman R.B., Health-Information Altruists
— A Potentially 
Critical Resource. NEJM, 2005. 353 (19): p. 2074-2077
6 www.d-grid.de

This work was supported by the D-Grid Project MediGRID,
funded by the 
Federal Ministry of Education and Research (BMBF), FKZ
01AK803A-H.

The Grid has emerged as a technology aiming at enabling
resource sharing and
coordinated problem solving in dynamic multi-institutional
virtual organizations [6],
[8]. Grids are used to join various geographically
distributed computational and data
resources, and deliver these resources to heterogeneous user
communities. While the
initial research on Grid computing was focused mainly on
providing a seamless access
to a heterogeneous suite of computational and data
resources, current efforts are
addressing the provision of a global distributed
infrastructure based on service
oriented paradigm. More and more grid toolkits are nowadays
are following a service
oriented approach by exposing and handling resources as
services. However a flexible
service Grid is not possible without support by semantic
technologies which lead to
what is know as Semantic Grid. Semantic Grid comes as an
extension of current Grid in
which information and services are given well-defined
meaning [4]. Knowledge about
resources is exposed and handled explicitly thus allowing a
certain degree of
automation in realizing various tasks on the Grid.
Furthermore, the information which
is going to be manipulated in a service Grid has to be
semantically described. This
will allow services to better interpret and manipulate the
content of the information
they are processing.

In our ongoing work in GRISINO project [1] - Grid semantics
and intelligent objects,
we aim of integrating three leading edge technologies which
complement
each other, for the definition of intelligent and dynamic
business and scientific
processes: (1) Semantic Web Services (SWS) as the future
standard for the
declaration of web-based semantic processes, (2) Intelligent
content objects as
the unit of value which can be manipulated by semantic web
services and (3)
Grid Computing as a pervasive service distribution
infrastructure for a future,
ambient intelligence space.

Grid computing is a central pillar for our GRISINO platform,
providing a
computational and organizational infrastructure. It can be
seen as the resource
backbone of GRISINO platform in terms of computational and
storage power.
The present abstract summarizes the authors initial ideas on
how Grid computing, as
one fundamental pillar of GRISINO platform, will be
integrated with Semantic Web
Services and Intelligent Content Objects in order to provide
platform which supports
intelligent and dynamic business and scientific processes.

The reminder of this abstract is structured as follows.
First we describe our initial
ideas on how Grid computing and Semantic Grid as its
semantic extension could play
the role of a hosting infrastructure for Semantic Web
Services. Then we point the
need of Grid computing as a supporting infrastructure for
Intelligent Content Objects
and how these technologies could be integrated. Finally we
conclude our paper by
pointing out the fundamental role of Grid computing as a
foundation block of our
infrastructure.

1 Grid computing and Semantic Web Services

Among the technologies which are nowadays following a
service oriented paradigm, Web
services and Grid computing have the biggest impact both on
academia and industry. A
closer look at Web services and Grid computing shows that
these two areas have a lot
in common. A resource on the Grid can be view as a service.
Latest directions in Grid
and Web services [3] provide a uni¯ed framework that deals
with both Grid and Web
services requirements. What is missing is a proper support
for machine processable
semantics and therefore human intervention is needed to
actually discover, combine,
and execute services. Semantic Web services promise to
solved this problem by
providing a fully mechanized web infrastructure for
computers interactions [5].

By using semantic technologies the Semantic Grid vision can
be achieved. For example,
ontologies, which provide machine understandable
terminologies, will be used to
describe resources and services on the Grid. The Semantic
Grid will be a grid of
services semantically annotated. Both domain ontologies
(e.g. physic, biology
ontologies) and infrastructure onotlogies (e.g. virtual
organiation ontologies,
service ontologies) will be required. They will allow a
sertain degree of automation
for tasks like Grid service discovery or negotiation of
service level agreements. All
these tasks can be potentially enhanced using the
functionalities provided by SWS
technologies.

Another possible integration point is around the Open Grid
Service Architecture
(OGSA) [7]. The OGSA framework, a conceptual model for
Grids, defines a set of
services which are needed for grid applications. However,
OGSA doesnt provide a
formal way to describe these services, thus being of little
use in automatic
performance of different service related tasks. One
particular way to realize the
(Semantic) Grid vision by integrating support for SWS into
current Grid architectures
is to semantically enhance current OGSA services, as for
example infrastructure, data
or information services. Last but not least all domain grid
services which will use
the Semantic Grid infrastructure will be annotated with
semantic descriptions.

2 Grid computing and Intelligent Content Objects

Intelligent Content Objects can be seen as semantically
described and annotated
content. In GRISINO, Intelligent Content Objects will be
produced and manipulated on
a large scale by applications, agents and services hosted by
the GRISINO
infrastructure. Given this high scale dimension in terms of
computation and storage,
Grid computing is a natural choice to follow. 

Huge amounts of Intelligent Content Objects or KCOs will
likely be stored on a
special form of grids called Data Grids [2]. They will allow
fast storage, indexing
and retrieval of content information in a short amount of
time. For example an
intelligent content object capturing information about a
movie can be replicated or
transformed using different services. The space needed to
store these objects grows
along with the number of operations invoked on these
objects. Therefor a huge amount
of disk space is required which can be hopefully provided by
the Data Grid.

The huge amount of storage capabilities is not the only
aspect where Grid and
Semantic Grid technologies could could empower our GRISINO
infrastructure. The other
huge scale dimension aspect relates to the huge
computational capabilities provided
by Grid. This integration dimension between Intelligent
Content Objects and Grid
Commuting will also be investigated in our integration
solution. Coming back to our
previous example it is likely that an intelligent content
object capturing
information about a movie will require allot of
computational power when processed by
services hosted by GRISINO common system infrastructure
(e.g. a movie rendering
service). Such power could be easily provided by a
Computational Grid that exposes
computers and computers clusters as a uniform accessible
computational platform.

3 Conclusion

Finally, we believe that the research in Semantic Web
Service provide a solid basis
for an integrated service oriented Semantic Grid.
Furthermore we believe that the new
Semantic Grid infrastructure which will emerge by combining
Grid and Semantic Web
services will provided a robust and flexible infrastructure
for intelligent
manipulation of information content. Our work on the
integration aspects mentioned
above has just started. We plan to further investigate the
integration points
previously mentioned and to prove our ideas by developing an
experimental testbed -
the GRISINO platform.

4 Acknowledgements

The work is funded by the FIT-IT (Forschung, Innovation,
Technologie - Infor-
mationstechnologie) under the project GRISINO - Grid
semantics and intelligent
objects. The authors would like to thank all the people who
are involved in
GRISINO project and the funding support from Austrian
Government.

References
1. Grisino, http://www.grisino.at (last accessed: 31.08.2006).
2. A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and
S. Tuecke. The data
grid: Towards an architecture for the distributed management
and analysis of large
scientific datasets, 1999.
3. K. Czajkowski, D. Ferguson, I. Foster, J. Frey, S.
Graham, I. Sedukhin, D.
Snelling, S. Tuecke, and W. Vambenepe. The WS-Resource
Framework, July 2004.
4. D. de Roure, N. Jennings, and N. R. Shadbolt. The
Semantic Grid: Past, Present,
and Future. In Proceedings of the IEEE, VOL.93, NO.3, 2005.
5. D. Fensel and C. Bussler. The Web Service Modeling
Framework WSMF. Electronic
Commerce Research and Applications, 1(2):113{137, 2002.
6. I. Foster and C. Kesselman. The Grid: Blueprint for a New
Computing Infrastruc-
ture. Morgan Kaufmann, 1999.
7. I. Foster, C. Kesselman, J. Nick, and S. Tuecke. The
Physiology of the Grid: An
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Integration, 2002.
8. I. Foster, C. Kesselman, and S. Tuecke. The Anatomy of
the Grid: Enabling Scalable
Virtual Organizations. Lecture Notes in Computer Science,
2150:1{26, 2001.

During september 2007 the LHC accelerator will start its
activity.
CMS, one of the four LHC experiment, will produce a large
amount of data that should
be stored and analyzed.
The CMS computing model is based on the grid paradigm: data
are spread
and accessed on a number of geographically distributed
computing centers.
Until real data are not available, the CMS community needs
simulated data to study
the detector response, the forseen physics interaction and
to get experience with
management and analysis data. So a large number of simulated
data are produced and
distributed among computing centres. Real data will be
analyzed by physicist at an
expected rate of ~100000 jobs per day using the grid
infrastructure.
To reach this analysis goals, CMS is developig CRAB (Cms
Remote  Analysis  Builder),
a user friendly tool to allow a generic users without
knowledge of grid
infrastructure to access data and perform its analysis as
simply as in a local
environment.
CRAB is deployed by CMS to access remote data and it takes
care to interact with all
Data Management services, from data discovery and location
to output file management.
An overview of the current implementation of this tool, its
interaction with grid
middleware and its usage is presented in this work.

Currently the largest Grids lack  an appropriate level of
the Quality of Service
(QoS) in two ways:  due to size and complexity the Grid is
not enough reliable  and a
 simple,  batch-oriented  processing model  is suboptimal
for  a number of 
applications. User-level scheduling  is a light software
technique that enables new
capabilities to be added and QoS  characteristics and 
reliability to  be improved, 
on top  of the existing Grid middleware and infrastructure.

User-level  scheduling  techniques  may  be  used to  reduce
 the  job turnaround 
time and  to provide  a  more stable  and predictable  job
output  rate. Splitting 
the processing  into many  fine-grained tasks improves  the
load  balancing and 
ensures that  the worker nodes  are used
efficiently. As the result the  computing resources may be
returned to the Grid
faster. We discuss the implications of this technique for
the users, the application
developers and the resource providers.

Applications which have been  interfaced with the user-level
scheduler follow the
master/worker model and include  High Energy  Physics data 
analysis, Monte  Carlo
simulation, Biomed  applications and  others. Distributed 
frequency  analysis for
the ITU and the autodoc-based drug discovery are the recent
large-scale activities
which are discussed in separate talks during the conference.

In the context of bioinformatics laboratory research,
measurements from experiments
can range dramatically in their accuracy and
reproducibility, forcing  researchers to
design experiments with more biological replicates. However,
statistical processing
systems can overcome this problem by widening the amount of
data they are able to
consider, but cost remains a strong limit on the size of
experiments. As a more
general solution, similar data may be collected across
several acquisition
facilities, but, in order to be able to reproduce or compare
different experimental
setups, side conditions associated to experiments must be
accurately tracked.
Moreover, end-users may be provided with different analysis
algorithms by different
providers, and search tools may be needed to find data and
applications. Eventually,
data or experimental setups as well as results from
experiments should be collected
through a user-friendly web interface.
Starting from these considerations, we decided to implement
a Grid-based data storage
and management system for data concerning bioinformatics
experiments. Indeed, a Grid
service based approach may provide a shared, standardized
and reliable solution for
storage and analysis of the above mentioned biological data.
Moreover, a Grid portal
may allow unpractised users to store their experimental data
on a complex storage
system and to access distributed data and services. Instead
of developing a database,
data and experiment annotations can be stored using metadata
management tools,
providing high flexibility and assuring experiment
replication for biological
research activities. Security and privacy issues can be
addressed using a
certificate-based authentication schema coming out for free
from the Grid technology
and sensible data can be federated or accessed without
moving them or via volatile
copies.
The described environment relies on storage services (with
replication and catalog
services) provided by the gLite Grid middleware. Through the
AMGA metadata catalog,
gLite is able to exploit the added value of metadata, in
order to let users better
classify and search experiments. The key feature in our
solution is that data files
can be searched and accessed just by providing their
description metadata. Several
keywords (metadata fields) are associated to data files and
the metadata catalog
collects such high level descriptions. Files are physically
stored on the Grid, and
the metadata catalog has also the information for accessing
them, through their
logical file name, without taking care of filesystem
structures. This way, files
could be replicated on disks to achieve more reliability but
the file collection is
kept consistent.
From a functional point of view, the adopted framework is
deployed in the form of a
Web Grid application visible to users as traditional web
pages, but it is ready to be
deployed also as a grid service exposed to the public with
standard interface (WSDL).
A Web interface has been implemented in order to hide the
complexity of framework and
to make users able to use a standard browser for navigating
a Grid portal and for
accessing available data services. From a data point of
view, the proposed
environment permits users to upload/download their data and
results on/from the Grid
Portal and to store them on Grid storage resources. The
filesystem complexity is
hidden by the AMGA representation, thus allowing also a
multiple perspective access
to data collections.
The same framework can be adopted in a biomedical scenario
combining text data for
patients, studies, and reports, as well as medical imaging
acquisition volumes, and
time series signals or genomic information.

Grid technologies have reached a high level of development,
but adopters underline
core shortcomings related to security, trustiness, and
dependability of the Grid for
commercial applications and services. Service Level
Agreements (SLAs) should be used
to define the quality of service for a job execution.
However, providers are still
cautious on adoption as agreeing on SLAs including penalty
fees is a business risk:
system failure, operator unavailability etc. can lead to an
SLA violation. AssessGrid
will address the risk awareness and consideration in SLA
negotiation, self-organising
fault-tolerant actions, and capacity planning. Risk
assessment methods will serve
providers as decision support for accepting/rejecting SLAs,
for price/penalty
negotiation, for activating fault-tolerance actions, and for
capacity and service
planning. A confidence service will be developed in
AssessGrid for supporting
customers in the estimation of provider’s reliability.
The AssessGrid results will support all Grid actors by
increasing the transparency,
reliability, and trustworthiness as well as providing an
objective foundation for
planning and management of Grid activities.

Cardiology Services involve multiple Specialist Medical
Disciplines and a wide
variety of related procedures. Some Services must be
provided locally, e.g.,
invasive, while others can be provided remotely, e.g., most
non-invasive can be
provided in part remotely. All such Services are key
elements in medical diagnoses
and procedures associated with the Heart and Cardiovascular
System. In modern Medical
Practice each Service is infused with an Information
Technology component, required
by Law or Practice.
Internet-based Services have been developed to assist
Researchers, Practitioners and
Patients. The Nurse-ECG Internet Service is presented. Its
User Community includes
Researchers, Practitioners and Patients. The major
limitation is geographic. The
Value-Added by such systems increases substantially when
support and accesibility is
available globally on a 24/7 basis. The EGEE Grid offers
such a pathway and potential
growth.
Basic requirements for a global Nurse-ECG System are
presented. They are heavily
influenced by the demonstrated need for real-time
interpersonal communications and
Electronic Healthcare Records for all members of the User
Community.

We present the AMGA Metadata Catalogue, which was developed
as part of the EGEE
(Enabling Grids for EsciencE) project's gLite Grid middleware. 
AMGA provides access to metadata for files stored on the
Grid, as well as a
simplified general access to relational data stored in
database systems. Design and
implementation of AMGA was done in close collaboration with
the very diverse EGEE
user community to make sure all functionality, performance
and security requirements
were met. In particular, AMGA targets the needs of the High
Energy Physics user
community to rapidly access very large amounts of metadata
as well as the needs for
security of the biomedical community. AMGA therefore tightly
integrates fine grained
Access Control List based security making use of a Virtual
Organisation management
system. In addition, AMGA offers advanced federation and
replication features to
increase dependability, performance and data security.

This contribution describes accomplishments achieved by the
computational chemistry
community utilizing computational resources and corresponding
applications within a grid environment of the Virtual
Organization 
for Central Europe (VOCE). VOCE infrastructure, part of the
EGEE II Grid,
currently consists of computational resources and storage
capacities provided
by the Central European resource owners. VOCE currently
provides a complete 
grid infrastructure running all necessary grid services
helping thus
scientists to solve their research projects and problems.
One of the currently
intensively studied areas of modern material design and drug
discovery is 
chemistry of interlocked supramolecules and their mutual
interactions. 
In the presented work, we investigate rotaxane, a
supramolecular complex. 
Rotaxanes are interlocked molecules in which macrocycle (the
'wheel') is 
threaded by a long 'axle' component. Our system consists of
a molecule 
cucurbit[7]uril (CB7) and a 4,4'-bipyridinium derivate.
Experiments show a 
switch-like movements along the axle in this supramolecular
complex.
To give a detailed insight to the switch-mechanism we calculated
the free energy profile along reaction coordinate related to
this movement. 
The evaluation of the free energy is a computationally
demanding task requiring
extensive computational resources due to necessity to
properly sample large 
phase-space. Currently used methods for the free energy
estimations 
(such as umbrella, bluemoon or adaptive biassing force
method) require 
a calculation of a huge amount of middle-length molecular
dynamic simulations which can run independently in parallel.
Therefore,
these types of computational tasks are very well suited to
exploit
large grid environments like the VOCE. The complete solving
of the described 
research problem comprises approximately hundreds thousands
of CPU hours at
1.6 GHz CPU with 1 GB RAM. Our results clearly demonstrate
that the VOCE Grid 
is the place where challenging applications requiring
advanced computational 
chemistry techniques can be easily utilized and
corresponding research problems 
successfully solved.

GENIUS is a powerful Grid Portal jointly developed by INFN
and NICE srl within the
INFN Grid Project . It provides to end users secure,
uniform, pervasive and
ubiquitous access to distributed, high-end computational
resources, services and
applications through a standard Web browser or through a
flexible Web Services interface.

EnginFrame and GENIUS greatly simplify the use of
Grid-enabled applications and
services, so they have been adopted by several important
industrial companies all
over the world and by many leading research & educational
institutes.
In particular GENIUS has been installed in many EGEE sites,
with satisfaction of
users and site managers and has been a core technology in
the context of the GILDA
dissemination testbed.

GENIUS allows to expose gLite-enabled  applications via
Web-browser or Web Services
and, using different EGEE services, provides the users with
a wide range of
facilities to run jobs and to manage their own data in a
very simple way.

Based on the latest version of the EnginFrame framework by
Nice srl, the GENIUS
Portal can run services on a broad range of different
computational systems including
gLite, Platform LSF, Sun Grid Engine, Altair PBS, Globus, etc.
It supports several open and vendor neutral standards and
seamlessly integrates with
JSR168 compliant enterprise portals, distributed file
systems, GUI virtualization
tools and different kinds of authentication systems
including Globus GSI, MyProxy,
VOMS extensions and a wide range of enterprise solutions.

Thanks to work done during the last year, GENIUS fully
supports the latest release of
the gLite middleware. In particular it now allows to submit
and manage jobs in
queues, supporting different flavours like DAGs, Job
Collections and, in the next
future, Parametric Jobs. It also provides data management
functionalities towards LFC
Catalog and supports AMGA client integration.

Looking at the future of GENIUS, many important features are
under analysis and
evaluation. 

Interoperability among different flavours of Grid middleware
is one of the most
important challenges GENIUS/EnginFrame is going to face. In
particular, in the
context of the A-WARE European project, a common interface
will be provided to access
gLite, Unicore/GS (DEISA project) and GT4 (TeraGrid project). 

Moreover the main goal of the A-WARE project is to develop
and integrate services at
a higher level in a Service-Oriented Architecture (SOA)
context providing workflow
orchestrations and workflow design capabilities, hiding the
underlying complexity of
atomic job submissions to end users.

There are three main nuclear fusion applications to run on
Russian Data Intensive Grid 
infrastructure at this moment and in the nearest future:
1. Plasma devices (stellarator) numerical optimisation; 
2. ITER facility engeenering computations: propagation of
waves in different plasmas;
3. Simulation and data processing for finding reduced models
suitable for plasma
real-time control.

The first application was presented on the 1st EGEE Users Forum.
The presented genetic optimisation method have proved it's
effectiveness in grid
environments. 
Thus, a lot of optimisation tasks from a variety of
scientific and engeneering areas
may be solved 
the same way.
The software elaborated for this application should be
refactored to be more user
frendly and 
robust.

The second and the third applications are in the process of
porting into the grid
environment. The 
ports should demonstrate a grid effectiveness in the two cases:
- large engineering variation computations;
- natural science data mining for construction of
phenomenological models.
The first applications' grid runs are expected to be carried
out until the end of 2006.

ELFI is a filesystem interface to the LFC catalog and
LCG/EGEE SE (both classic and
SRM v2).

With ELFI, you can see the entries in the LFC catalog as
files in a locally-mounted
filesystem, and directly operate on the replica
contents: read/write operations on the local filesystem are
acted as read/write
operations on a remote SE via the GSI-RFIO protocol.  All
operations on the catalog
or the SE have a local filesystem equivalent.

ELFI features:

      * Transparent file access via LFN only

      * Posix ACL support

      * Posix IO operations (throug gsi-rfio transport protocol)

      * Classic SE, SRM v2.1.1 and SRM v2.2 support

      * replica management via filesystem commands (``ln''
command)


The ELFI filesystem process runs entirely in user-space: it
uses the standard FUSE
(http://fuse.sf.net) userland filesystem framework.

An integrated framework, based on EGEE tools, providing
respectively a credential
authority (VOMS), a policy-based authorization system
(G-PBox) and an accounting
system (DGAS). This framework enables VO/experiment to build
groups of users, assign
roles and associate policies and quotas to each group and
role in a dynamic way,
implementing an automatic way to enforce agreements with the
resource owners.

Current developments in the world of HEP-based grid
computing have put an accent on
the need to differentiate user jobs on the basis of
group/role membership, creating
in effect several classes of service, each with its own
specific configuration, and
the need to have a fair-share mechanism in place to permit a
full and fair use of
available resources. This poster shows a policy-based
solution of this problem, whose
main features are a high configurability and the capacity to
change mappings between
groups and classes on the fly, without requiring a
reconfiguration or a stop of the
services.

Mathematical modeling of a living cell is a great challenge
for modern science. The
creation of integrated model of eukaryotic cell is the aim
of the Mathematical Cell
(MathCell) project (http://www.mathcell.ru) realized at the
Institute of Mathematical
Problems of Biology RAS during the EGEE Project. It includes
3D interactive living
cell model, encyclopedia on mathematical modeling of cell
and software for modeling
of basic processes in living cell. Within the limits of the
Project the interactive
environment was developed, which allows to perform
calculations of some mathematical
models in GRID infrastructure. Further development of the
MathCell project implies
integration of individual components of the model into a
program system which would
simulate cell processes at different levels – from
microscopic to macroscopic scales
and from picoseconds to the cell lifetimes. Such modeling
will allow ones to solve a
number of practical problems, for example, acceleration of
development of novel drugs
and of prediction of their direct and mediated action,
development of thin
biochemical agents which will influence on metabolic
reactions in the organism.
Besides such model will be useful by development various
nanostructures and
nanomaterials - in the most advanced researches which are
having for an object
creation nanorobots which at a cellular level will work with
a view of medicine and
preventive maintenance of illnesses. This work will
naturally require combining of
resources provided by EGEE-II Project and their merging into
an integrated
computational environment.

The CDF Collaboration is moving beyond the used dedicated
resources and starts
exploiting Grid resources due to the large increases in
computing requirements.
CDF has been running a set of CDF Analysis Farm (CAFs),
which are submission portals
to dedicated pools, and LcgCAF is basically a
reimplementation of the CAF model in
order to access Grid resources by using the LCG/EGEE
Middleware components. LcgCAF is
constituted by a set of services each of them responsible
for accepting, submitting
and monitoring CDF user jobs during theirs lifetimes in the
Grid environment.
This poster presents an overview the LcgCAF architecture
within the LCG/EGEE Middleware.
The performances on Monte Carlo production using this portal
are also shown together
with future improvements.

Overview and status of the Bioinformatics Applications in EGEE-2

Biological data are most times published and then become public ones. They, then, do
not need to be isolated or encrypted. But, in some cases, these data stemed from
patients or are analyzed with, for instance, pharmaceutical or agronomics goals. Also
in simple ways , these data, before to become public, have to be kept confidential
while researchers haven’t been able to publish their work or to register them. So
they are a lot of cases where the integrity and the confidentiality of biological
data have to be protected against unauthorized accesses. But, as these private data
are also large datasets, they need high-throughput computing and huge data storage to
processed, such as ones produced by complete genome projects. These requirements are
enhanced in the context of a Grid, where the computing and storage resources are
distributed across a large-scale platform. We have developed a distributed service to
securize biological data on grid: the EncFile encrypted files management system. We
have used it on the production platform of the EGEE grid project. Thus we provided
grid users with a user-friendly component that doesn’t require any user privileges.

One of the problems encountered while porting, in the
framework of the BIOINFOGRID EU
project, bioinformatics applications to the GRID, concerns
their input-output.
Many of the widely used tools in bioinformatics, have been
developed when the grid
technology was not yet established, so they  make their
input out from the computer
local disk.
To port  such an application on the  grid, one has to handle
case when the WN local
disk has a local disk not sufficient to contain the job
input output files as well as
cases when the WM is completely disk less.
In such cases it is difficult to change the application
code, which generally was not
developed by the researcher, and sometimes it also difficult
 to make use of specific
libraries that could allow the remote file access.
Parrot represents a possible solution to the problem since
it allow the  use of a
variety of protocols to map the file-system call, such for
example gridftp and http.
We will report on a development to further improve the
versatility of Parrot and its
usability on the EGEE infrastructure. In particular we have
developed a plugin for
Parrot which uses the GFAL API directly. In this case the
application can run using
only the Logical File Name (LFN) of the required input
output  files and does not
have to worry about the details of the underlying storage
system use in the EGEE grid.
Along the same line we have also developed a similar
filesystem which will use GFAL
API and  FUSE. As FUSE is  the most widely used system to
use remote file services as
a local file on linux. Fuse also has been integrated in
linux kernel and this makes 
more easy to implement it on linux environment.
Now we are involved in an intense testing of both the two
implementation.
The most important Grid services involved in this work are
the Storage Services and
the File Catalog Services.


References:
1) Parrot: http://www.cse.nd.edu/~ccl/software/parrot/
2) FUSE: http://fuse.sourceforge.net/

Bioinformatics analysis of data produced by high-throughput biology, for 
instance genome projects [1], is one of the major challenges for the next years. 
Some requirements of such analysis are to access up-to-date databanks 
(of sequences, patterns, 3D structures, etc.) and relevant algorithms (
sequence similarity, multiple alignment, pattern scanning, etc.) [2]. Since 1998, 
we are developing the NPS@ Web server ([3], Network Protein Sequence 
Analysis), that provides the biologist with many of the most common resources 
for protein sequence analysis, integrated into a common workflow. These 
methods and data can be accessed through simple web browsing and HTTP 
connection, or througth high-level bioinformatics interface like MPSA or 
AntheProt programs.

GPS@ Web portal (Grid Protein Sequence Analysis, http://gpsa-pbil.ibcp.fr) is 
the grid-enabled release of the NPS@ bioinformatics portal. GPS@ hides 
mechanisms required for submitting bioinformatics analyses on the grid 
infrastructure. By simply selecting the “EGEE” check-box, GPS@ will schedule 
the submission of the BLAST computation on the EGEE grid when clicking on 
the “submit” button. The bioinformatics algorithms and databases available on 
GPS@ have been distributed and registered on the grid and GPS@ runs its own 
EGEE interface to the grid.

GPS@ portal makes the Bioinformatics job submission easier on the grid, and 
provide biologists with the benefit of the EGEE grid infrastructure to analyze 
large biological dataset: for example including several protein secondary 
structure predictions into a multiple alignment, or clustering a sequence set by 
analyzing, with BLAST or SSEARCH, each sequence against the others.

[1]	Bernal, A., Ear, U., Kyrpides, N. : Genomes OnLine Database (GOLD): a 
monitor of genome projects world-wide. NAR 29 (2001) 126-127
[2]	G. Perrière, C. Combet, S. Penel, C. Blanchet, J. Thioulouse, C. Geourjon, J. 
Grassot, C. Charavay, M. Gouy, L. Duret and G. Deléage, Integrated databanks 
access and sequence/structure analysis services at the PBIL. Nucleic Acids Res., 
31:3393-3399, 2003.
[3]	Combet, C., Blanchet, C., Geourjon, C. et Deléage, G. : NPS@: Network 
Protein Sequence Analysis. Tibs, 25 (2000) 147-150.

The vast amount in complexity of data generated in Genomic Research implies that new
dedicated and powerful computational tools need to be developed to meet their
analysis requirements. Blast in Grid (Big) is a Grid- enabled Blast service that
enables bioinformatic users to deal with datasets up to the order of hundreds of
thousand sequences. Many efforts have been done in the literature concerning the
speeding up of Blast searches, but few of them deal with the use of large
heterogeneous production Grid Infrastructures.
These are the infrastructures that could reach the largest number of resources and
the best load balancing for data access. The Grid Service under development will
analyse requests based on the number of sequences, splitting them accordingly to the
available resources. 
Lower-level computation will be performed through MPIBLAST. The software architecture
is based on the WSRF standard.

Bringing 3D-EM to the Grid.
---------------------------

3D-EM is a well established technique that allows us to
visualize biological
structures across a wide range of sizes. As such, it
provides a bridge 
between more fine-grained techniques (such as X-ray
crystallography or
NMR) and coarser methods like traditional light microscopy,
making 
an un-substitutable tool for understanding subcellular
structures and 
macromolecular assemblies. Its main downside being the heavy
demands on 
compute power at some steps of the analytical process.

We have undertaken the project of bringing 3D-EM techniques
to the Grid.
Initial tests with 3D reconstruction yielded poor speedup
results turning
up important lessons for subsequent work. We are now dealing
with ML 
classification of data, proceeding to refactor Xmipp and
dealing with 
the major blockstoppers detected. Still, some relevant
issues worth noting
still remain that result in major conceptual challenges.

In this presentation we deal with the general problem of
3D-EM in its
experimental context, describe our approach, preliminary
results and
directions for future work.

Modelling and simulation techniques are valuable tools for the understanding of
biological systems. Such systems can be described by a set of constraint biochemical
reactions and translated into a system of differential equations. Each reaction has
substrates and products with given stoichiometries, and modifiers or catalysts that
affect the reaction kinetics. Often the topology of these biochemical reaction
systems is known and available from databases, but the detailed reaction kinetics and
their kinetic parameters are not well known. To overcome this problem we propose a
Monte-Carlo approach, where we simulate different biological scenarios of certain
interest with kinetic parameters chosen from a given random distribution. By
repeating these simulations several times with different sets of kinetic parameters
differences in the behaviour of the different models that reflect certain biological
scenarios can be identified. Depending on the size of the model a single simulation
can take several minutes to up to an hour so that for this approach an immense
computational power is required. To do this in a maintainable time a parallelisation
of the approach is required. We will present this approach and its realisation using
the EGEE grid technology.

Presentation of the EELA project, E-infrastructure shared between Europe and 
Latin America,  status and perspectives of the biomedical applications.

The LIBI (International Laboratory for Informatics) is a
project,  leadED by PROF.
CECILIA SACCONE of the Institute of Biomedical Technologies
of the italian National
Research Council (CNR) and supported  by the Italian 
Minister for Research, which
collects leading italian institutes in bioinformatics
working together with
technological partnerS with the aim to built a  virtual
Laboratory with a modern
infrastructure supporting the life science  research in Italy.
For its HT, high throughput, applications, LIBI has adopted
the gLite  Middleware and
the EGEE infrastructure:  a farm with 28 CPU is already part
of the EGEE grid branch
managed by the italian ROC.
The use of the grid technology by the LIBI, is dictated by
the enormous computational
resources required by particular applications. For example
the GenoMiner  application
 (Castrignanò et al., 2006) intends to carry out
cross-genome comparisons with the
aim to detect highly conserved sequences, LIKELY INVOLVED IN
CODING OR REGULATORY
ACTIVITY.  A complex procedure has been  ADOPTED  in order
to improve the speed of
the comparison and to limit the search to selected parts of
the genomes. However, the
grid is needed to validate the entire procedure. For this
reason a grid application
has been set up to compares each tract of the human genome
with the whole rat genome.
An overall number of more of 2000 Million sequence
comparison is required, where each
of them can take up to 2-3 seconds.
In order to keep track of the comparison correctly executed
a  "task-queue"  schema
based on Database server suitably implemented. The
"task-queue" is capable of
managing multiple dependencies between tasks, it keeps
tracks  of the grid-job-id to
which is demanded the execution of a specific task. It keeps
also track of the number
of attemptS to execute a particular task in order to avoid
the resubmission of jobs
that "always" fail.
There is also the possibility to choose the priority of some
of the tasks in order to
run them in the correct sequence.
The DB server used by the task queue can also be used to
monitor the status of the
application. This feature gives the possibility to the user
to control the status of
all the jobs  running and executed in a very easy way.
The main Grid Services used by this application are the
Storage Services, to collect
the the huge amount of output date produced by the
application, and  the Workload
Management System  to choose the best farms with free CPU's
that can run the
application and  to transport in a reliable way the crucial
files needed on the WN.
The challenge is actually running on the Italian gLite
infrastructure (INFN-GRID):
more then 450 thousands sequences comparisons have been
performed in a month time.


References: 
1) Castrignano T, De Meo PD, Grillo G, Liuni S, Mignone F,
Talamo IG, Pesole G.
GenoMiner: a tool for genome-wide search of coding and
non-coding conserved sequence
tags. Bioinformatics. 2006 22(4):497-9.
2) LIBI: http://www.libi.it/
3) CSTminer:
http://nar.oxfordjournals.org/cgi/content/full/32/suppl_2/W624

Conclusion and perspectives about Bioinformatics activity in EGEE-2.

We will briefly review the process, and discuss any 
outstanding points.

Presentation of plans for vulnerability testing

DSA1.3, "Grid Services Security Vulnerability and Risk 
Analysis" is a Month 10 deliverable of task TSA1.4.2. 
We should discuss the table of contents and how it is 
produced.

This will be an open discussion on the next steps on the
path towards a European Grid Initiative. Forming an
Association of NGIs or an Association for the promotion 
of NGIs will be discussed. Note that a next workshop on 
EGI will be organised at the end of this year or the
beginning of next year.

GridwiseTech, the independent expert in Grid technology
succeeded in  connecting the first large industrial customer
to the EGEE  infrastructure.

LHC Computing Grid Project (LCG) is said to be the first
worldwide  deployed Grid production system, so far mainly
serving academy.  However, with thousands of distributed
assets interconnected with  unconventional technology, it
has great potential to become virtual  hub for businesses,
the role that Stanford had for what later become  the
Silicon Valley.

GridwiseTech, recently awarded as top innovator for
deploying  scientific results in industry, helps companies
to hook up to the  EGEE infrastructure in the process of
virtualizing their infrastructure.

In this presentation, GridwiseTech's Tomasz Szepieniec will
explain  how we made the large European corporation use
LCG-enabled resources  for their engineering needs,
potentially reducing the design cycles  from months to
hours. Our solution can easily serve other industrial 
customers, thus creating foundations for Europe-wide
business grid.

CERN openlab II is a partnership between industry and CERN
with an aim to demonstrate the relevance of new and
innovative technological solutions for scientific computing.
Current partners are HP, Intel and Oracle. Inside openlab
two competence centres have been defined: a Platform
Competence Centre (PCC) with its main focus on the evolution
of the computing hardware and related software; and a Grid
Interoperability and Integration Centre (GIC) with a close
link to EGEE-II.
The talk will briefly explain the way industrial partners
can get involved with openlab and review the initial results
and future plans for the activities that are relevant to
Grid computing.

GENIUS is a powerful Grid Portal jointly developed by INFN
and NICE srl within the INFN Grid Project . It provides to
end users secure, uniform, pervasive and ubiquitous access
to distributed, high-end computational resources, services
and applications through a standard Web browser or through a
flexible Web Services interface.

EnginFrame and GENIUS greatly simplify the use of
Grid-enabled applications and services, so they have been
adopted by several important industrial companies all over
the world and by many leading research & educational institutes.
In particular GENIUS has been installed in many EGEE sites,
with satisfaction of users and site managers and has been a
core technology in the context of the GILDA  dissemination
testbed.

Based on the latest version of the EnginFrame framework by
Nice srl and thanks to work done during the last year for
supporting the latest release of the gLite middleware,
GENIUS now presents some new important features and
improvements and it is going to face key challenges as
interoperability between different flavours of Grid middleware.

The Business Track will conclude with a Panel Discussion
involving leading experts and chairs from the Business Track
who will evaluate the  previous sessions, the main
discussions and issues that have come out from each session.
The objective from here will be to develop recommendations
and next steps that build on the presentations case studies,
success stories presented and valuable knowledge exchange
that has take place over the two day business track.

The talk will present the status of the analysis of 
WISDOM-I results and the work being done within the 
BioinfoGRID project to deploy Molecular Dynamics 
computations on EGEE

The talk will provide an overview of the H5N1 data 
challenge deployed in April-May 2006. It will provide 
information on grid deployment metrics as well as 
information on the biological analysis going-on.

The talk will provide an update on the status of 
WISDOM-II, the next docking data challenge to take 
place from October 1st 2006. Information will be 
provided on the targets to be docked and the grid 
deployment strategies.

EUChinaGrid speaker

Meeting of COD-on-Duty teams operating the daily monitoring
of the EGEE/LCG grid:  feedback is collected, procedures and
tools are discussed and enhanced.

The EGEE project has created the largest production-level Grid
infrastructure in the world, which provides a level of
performance and
reliability never achieved before. The efforts made in the
project 
includes a wide range of activities from the deployment and
management 
of this vast infrastructure or middleware development, to
user training. 
Among them, application porting is of crucial interest to
the scientific 
community. In this context, we have seen a proliferation of
web portals 
and ad-hoc middleware developments to ease the use of Grid
by different 
scientist communities. However the actual infrastructure
lacks of a 
common, consistent and general application development
framework.

  The use of standard Grid Application Programming
Interfaces (APIs) 
could aid the rapid development and distribution of
applications across 
the Grid. Moreover, the use of a standard API will help new
users to 
port their applications to an unfamiliar environment; and
will minimize 
the impact of the modifications on the EGEE middleware, as the 
interfaces  would remain unchanged.

  In this sense, the Distributed Resource Management
Application API 
(DRMAA) GGF specification constitutes an homogeneous
interface to 
different Distributed Resource Management Systems (DRMS) to
handle job 
submission, monitoring and control, and retrieval of
finished job 
status. The DRMAA standard represents a suitable and
portable framework 
to express scientific distributed computations. Also, DRMAA
could reduce 
the application development cycle. A Grid application could be 
developed, tested and debugged using the organization local
cluster 
-DRMAA implementations includes Condor, SGE and PBS- and
then executed 
on the EGEE Grid using the GridWay Metascheduler.

  In this demonstration we will show how to use DRMAA to
develop Grid
applications. As an example we will consider a Fusion Ray
Tracing 
application, part of the NA4 Fusion activities. In
particular, we will 
use the DRMAA C and JAVA implementations provided by
GridWay, and 
resources from the Fusion VO. GridWay is an open-source
meta-scheduler 
which gives end users, application developers and managers
of Grid 
infrastructures a scheduling functionality similar to that
found on 
local DRMS. Additionally, we will show in this demonstration
GridWay 
scheduling and resource management functionality, and
command line 
interface.

The SPM software package, based on the comparison of the
candidate case to normal
cases through a Statistical Parametric Mapping (SPM)
algorithm, is largely used by
the neurological research community to quantify ipometabolic
patterns in brain
PET/SPECT studies for the early diagnosis of Alzheimer’s
Disease (AD). Since the
accuracy of ipoperfusion maps is strictly related to the
number of normal studies
compared to the test image,  a large set of images of normal
patients is required for
an accurate statistical analysis. However, due to ethical
issues and to high costs of
neuroimaging technologies, PET/SPECT studies for normal
patients are very rare.
Moreover, because of privacy and security issues, the images
of normal subjects
cannot be freely moved between sites or published by the
centre that collected them.
As a consequence, only doctors working at very large
institutions, locally owning
large databases of normal images, can usually carry out
SPM-based analyses. With our
application, doctors from small peripheral hospitals can
remotely access large sets
of normal PET/SPECT images provided by different medical
research institutes and
extract the information needed for the statistical analysis
without moving the
original image files. Grid technologies allow easy access to
distributed data as well
as to distributed computational resources. In order to
provide a user friendly
interface, remote access to SPM is being made available
through the Italian Portal of
Neuroinformatics. The portal contains a section entirely
dedicated to the statistical
analysis of PET/SPECT images, accessible by authorized users
only. Directly from the
portal, any authorised user can upload the suspect AD image,
select normal cases for
statistical calculation, and eventually collect the results
of analysis.
The basic steps of the Grid implementation of the SPM portal
service are listed below:
1.	Acquisition of the test image on the user node
2.	Transfer of the test image to the management node
3.	Query on DB catalogue of normal images on the management node
4.	Transfer of a small software executable for information
extraction to the
repository nodes
5.	Extraction from normal images of the information needed
for the statistical analysis
6.	Transfer of the extracted information to the management node
7.	SPM statistical analysis on the management node
8.	Transfer of SPM results to the user node
In many eHealth Grid applications, the crucial point is a
reliable and efficient data
and metadata management. In our application this is needed
for identifying suitable
normal images across hospitals. From a data management point
of view, the mandatory
requirements for the Grid implementation of the above
described SPM application are
the following: 
- resources and services for the storage of PET/SPECT images
on different Grid sites;
- data management services for the registration in a
catalogue and the association of
metadata to images.
Two different environments (gLite and AliEn) have been
experimented, especially as
regards their functionalities concerning the management of
metadata, enabling
institutions to choose the deployment that better fits their
needs and resources. In
both environments, integration with the portal allows
seamless GUI interaction with
the available functionalities from the catalogue, the
analysis software and portal
services. Through the portal users can transparently exploit
both systems. Both
environments have provided satisfactory results.

Malaria is a dreadful disease affecting 300 million people
and killing 1.5 million 
people every year. Drug resistance has emerged for all
classes of antimalarials 
except artemisinins. This example illustrates the real need
for new drugs 
against neglected diseases.
There are millions of chemical compounds available, but it
is nearly impossible 
and very expensive to screen such a high number of compounds
in the 
experimental laboratories by high throughput screening.
Besides the high 
costs, the hit rate is quite low [1]. An alternative is high
throughput virtual 
screening by molecular docking, a technique which can screen
millions of 
compounds rapidly, reliably and cost effectively. Screening
each compound, 
depending on structural complexity, can take from a few
minutes to hours on a 
standard PC, which means screening all compounds in a single
database can 
take years. Computation time can be reduced very
significantly with a large grid 
gathering thousands of computers [2].

In 2005, for the first time, we have been able to deploy
large scale virtual 
docking within the framework of the WISDOM initiative [3]
against plasmepsin, 
the aspartic protease of Plasmodium, responsible for the
initial cleavage of 
human haemoglobin [4]: more than 46 million ligands were
docked in less than 
6 weeks using about 80 years of CPU on the EGEE [5]
infrastructure. Up to 
1700 computers were simultaneously used in 15 countries
around the world. 
Commercial software with a server license was successfully
deployed on more 
than 1000 machines at the same time.
At the end of the large scale docking deployment, 100
compounds have been 
selected for post processing based on the docking score, the
binding mode of 
the compound inside the binding pocket and the interactions
of the compounds 
to key residues of the protein [6]. Some of the compounds
identified were 
similar to already known plasmepsin inhibitors, like the
Urea analogues which 
were already established as micro molar inhibitors for
plasmepsins. This 
indicates that the overall approach is sensible and large
scale docking on 
computational grids has real potential to identify new
inhibitors. In addition to 
this the Guanidino analogues are very promising and most
likely to become a 
novel class of plasmepsin inhibitors.
This success led to a second computing challenge targeting
Avian Flu 
neuraminidase N1 that required more than 100 CPU years on
the EGEE, 
Auvergrid and TWGrid infrastructures in April and May 2006
[7]. Potential drug 
compounds against avian flu are now being identified and
ranked according to 
the binding energies of the docked models. At least 50
compounds will be 
assayed experimentally at identified laboratories.

The WISDOM production environment was designed to achieve
production of a 
large amount of data in a limited time using EGEE, Auvergrid
and TWGrid 
middleware services. Three packages were developed in Perl
and Java. Their 
entry points are a simple command line tool. The first
package installs the 
application components (software, compounds database…) on
the grid 
computing nodes. The second package tests these components.
The third 
package monitors the submission and the execution of the
WISDOM jobs thank 
to the Workload Management System and the Data Management.
The used 
production service is LCG-2.

This abstract has presented pioneering activities in the
field of grid enabled 
virtual screening against neglected and emerging diseases in
Europe. These 
achievements demonstrated the relevance of large scale grids
for the drug 
discovery process and to enable world-wide and
multidisciplinary collaboration. 
Using the grid to identify the most promising leads for
biological tests speeds 
up the development process, frees up medicinal chemists’
time, and 
concentrates their biological assays in the laboratory on
the most promising 
components.

To illustrate the grid impact, a demonstration [8] will show
the number of 
compounds that can be docked on several grid infrastructures
during the 
conference time. Thousands docking jobs are submitted at the
beginning of the 
conference. The visitor can follow the progress of the
experiment during the 
conference time by a led display and several statistic
figures (success rate, CPU 
days consumed, number of jobs vs. site…). 
The strategy for virtual screening on the grid is presented
as well as the grid 
infrastructures used. The demonstration visualization will
be available during 
the conference time on http://wisdom-demo.healthgrid.org. It
receives the Best 
Demo Award during the Healthgrid 2006 conference. 


[1] R.W. Spencer, Highthroughput virtual screening of
historic collections on the 
file size, biological targets, and file diversity,
Biotechnol. Bioeng 61 (1998) 61-
67.
[2] A. Chien et al., Grid technologies empowering drug
discovery, Drug 
Discovery Today, 7 Suppl 20 (2002) 176-180.
[3] See http://wisdom.eu-egee.fr/ 
[4] V. Breton, et al., Grid added value to address malaria,
Proceedings of the 6-
th IEEE/ACM CCGrid conference (2006).
[5] F. Gagliardi, et al., Building an infrastructure for
scientific Grid computing: 
status and goals of the EGEE project, Philosophical
Transactions: Mathematical, 
Physical and Engineering Sciences, 363 (2005) 1729-1742
[6] N. Jacq, et al., Grid-enabled High Throughput Virtual
Screening, accepted for 
the proceedings of GCCB 2006, (2006)
[7] H.-C. Lee, et al., Grid-enabled High-throughput in
silico Screening against 
Influenza A Neuraminidase, Proceedings of the NETTAB 2006
workshop, (2006)
[8] N. Jacq, et al., Demonstration of In Silico Docking at a
Large Scale on Grid 
Infrastructure, Proceedings of Healthgrid conference 2006,
Studies in Health 
Technology and Informatics, 120 (2006) 155-157, PMID: 16823133.

The EGEE infrastructure is the largest production
infrastructure (over 200 sites, 
more than 15,000 CPUs and about 9 PB storage). High-Energy
Physics (notably 
the experiments at the Large Hadron Collider at CERN),
Biomedical applications, 
Earth Observation, Computational Chemistry and Nuclear
Fusion are depending 
on the EGEE infrastructure. 
The computational and storage capability of the Grid is
attracting more scientific 
and innovative applications. In this contribution we would
like to demonstrate 
the status of the EGEE-UNOSAT collaboration. 
UNOSAT is a United Nations activity to provide access to
satellite imaginary and 
geographic system services for humanitarian operations to
plan rescue or aid 
activities. UNOSAT is implemented by the UN Institute for
Training and Research 
(UNITAR) and managed by the UN Office for Project Services
(UNOPS). In 
addition, partners from public and private organizations
constitute the UNOSAT 
consortium. Among these partners, CERN participates actively
providing the 
computational and storage resources needed for their images
analysis.  Indeed 
through its partnership with CERN, UNOSAT is spearheading
the use of Grid 
applications for access to the images and use of
decentralized Geographic 
Information systems (GIS). 
Based on two successful CERN-UNOSAT pilot projects (data 
storage/compression/download and image access through mobile
phone), 
UNOSAT is seeking to consolidate the considerable work
undertaken so far in 
the present activity. 
The use case we would like to demonstrate is the delivery of
satellite images 
from the Grid to a portal (web and portable devices). In
particular, we would 
like to enable the selection and download of satellite
images starting on a 
portable device (using the GPS coordinates provided by the
device itself). The 
system provides seamless access to valuable satellite images
while preserving 
the security requirements of the data provider and of the
EGEE infrastructure 
(use of X509 certificates).
The system uses EGEE services already used by other
applications and our 
demo orchestrates them. The satellite images are catalogued
by the AMGA 
(Metadata) and LFC (location) services. The handling of images 
(compression/decompression, cropping, etc…) is provided by
the computational 
grid resources via the EGEE workload management system.
This work is being performed in close collaboration with the
NICE company, 
providing their EnginFrame technology (The technology used
by Genius EGEE 
Grid portal as well, for a development and deployment
environment for portal 
applications, with support for secure access to Grid
resources and a powerful 
toolkit for application development). 
We believe that this project is extremely interesting for
the UNOSAT community 
and the collaboration schema would also be very interesting
as a model for 
other applications supported by EGEE II.

Climate research is generally very data-intensive.
Observations, analysis and output
data of climate simulations are traditionally stored in
large archives and central
databases. In order to make this data searchable and
accessible for further analysis
and/or data comparison on the grid appropriate interfaces
between the existing data
storage systems and the EGEE infrastructure need to be
established. This interface is
realized in close collaboration with the German C3-Grid
project, which currently
establishes a common metadata model, and metadata publishing
infrastructure as well
as data access mechanism. With respect to metadata these
developments are based on
international standards like the ISO  19115 / 19139  XML
metadata schema and the OAI
(open archives initiative) metadata harvesting approach. For
data access a common
community web service interface is developed which triggers
complex data selection
procedures and makes the result available on gridftp
accessible storage.  

As a prerequisite for the data access a metadata catalogue,
containing information
for discovery and access of available datasets is needed. To
make the metadata
descriptions of the existing databases available on the EGEE
infrastructure the AMGA
catalogue is used. The catalogues is updated by means of XML
descriptions, which are
harvested on a regular basis from the existing datacenters.
The upload of discovered
data files from the external database to the EGEE
infrastructure is based on
webservices and gridftp: Based on information from the
metadata catalogue the
appropriate webservice endpoint is contacted from within an
EGEE data analysis job.
This webservice triggers data preprocessing functionality
and delivers the result to
a local gridftp accessible workspace from where they can be
retrieved, stored on an
SE and registered as EGEE accessible.

In order to exemplify the added value for the climate
community we will show
components of a complete workflow of searching, accessing
and analysing climate data
supported by the established interfaces.

Recent studies have suggested that the high pathogenic avian
flu H5N1 virus has the
potential of developing drug resistance and of acquiring the
ability of
human-to-human transmission. To enable biologists a better
response to the threat,
the second EGEE biomedical data challenge battling avian flu
was set to screen
300,000 compounds against 8 predicted mutations of the
Influenza A Neuraminidase for
analyzing the efficiency of the known drugs and for
searching new drugs. In April and
May 2006, we succeeded to mobilize over 2,000 CPUs in the
EGEE Grid infrastructure,
demonstrating that the high-throughput screening (HTS) of
drug analysis can be
efficiently reproduced on the Grid using the WISDOM platform
previously developed for
the Malaria data challenge in last Summer. The 6-weeks
activity has covered over 100
CPU years of CPU power required for the virtual screening
process and has produced
about 600 Gigabytes of docking results for further analysis.

Current computing model of the Grid-enabled HTS adopts a
coordinative way of
execution in order to gain the docking throughput; however,
to bring biologists a
real end-user application for their daily research, the
application usability needs
to be improved taking into account the realistic usage
patterns. For example, the
preparation and deployment effort needed for starting the
data challenge will not be
appreciated by the users who frequently repeat the virtual
screening for testing
their libraries and docking parameters. The batch mode HTS
is also not feasible for
interactive analysis which can save biologists’ time by
allowing them to start
analyzing partial results on the fly instead of dealing with
a huge amount of output
at the end. In addition, biologists prefer a graphical user
interface to configure
domain-specific parameters.

To improve the usability, we first introduced a light-weight
framework called DIANE
to enable the interactive analysis of the Grid-enabled
virtual screening application.
DIANE was originally developed for handling the distributed
applications within a
Master-Worker model. It provides an overlay system on top of
the Grid system, in
which the pull-mode scheduling and failure recovery
mechanisms are implemented based
on the CORBA protocol. On the other hand, the DIANE
framework hides the details of
the job operations on the Grid so that application
developers can concentrate on the
implementation of application logic, and end users benefit
from the simplified job
descriptions containing only intuitive and application
specific parameters. The
stability and efficiency of DIANE has been tested by taking
a significant part of the
avian flu data challenge.

Following the successful avian flu data challenge, the
Academia Sinica Grid Computing
Centre (ASGC) in Taiwan is in charge of developing a
user-friendly docking
environment leveraging on the DIANE framework. Building on
top of the DIANE
command-line interface, we have customized a web-based
interface for biology
end-users. Through the web interface, users can quickly set
a filter on compound
libraries, configure docking parameters, start-up and
monitor their virtual screening
activities on the EGEE production environment. During the
job execution, the
completed dockings are scored based on the binding energy.
The docking complexes are
available as soon as the results are produced; therefore
biologists can progress on
for further analysis without being blocked until their jobs
are finished. A
visualization interface of complex structures also aids
biologists in analysis.

Dashboard project for CMS and ATLAS experiments has to
provide a single entry point
for the monitoring information collected from the
distributed computing systems of the
corresponding experiment.
One of the main functionalities provided by the experiment
dashboard is job monitoring.
Dashboard job monitoring service presents a complete view of
the experiment activity
on the Grid infrastructure independently of the Grid flavour
and  compiles a
comprehensive picture of the overall success rate. 
Dashboard combines Grid-related
monitoring data and experiment specific information. One of
the main purposes of the
experiment dashboard is to indicate any job
submission/execution problem and to help
to identify the reason of the problem of any origin.
In addition to job monitoring experiment dashboard covers
other experiment activities
on the Grid, like for example data management for ATLAS and
data transfer tests for CMS.

Due to the dynamic and complex nature of the Grid, it’s not
easy to use it in a daily
work. To attract new users, especially from scientific
community, user friendly tools
are needed to simplify access to the Grid. To solve this
problem we introduce the
concept of Migrating Desktop Platform which is a graphical,
user oriented product
that simplifies the use of the grid technology in the
application area.
Migrating Desktop Platform (MD) is an advanced graphical
user interface and a set of
tools combined with user-friendly outlook, similar to window
based operating systems.
It hides the complexity of the grid middleware and allows to
access grid resources in
an easy and transparent way with focus on interactive and
parallel grid applications.
These applications are both compute- and data-intensive and
are characterized by the
interaction with a person in a processing loop. MD can
attract new users by its
features: easy to use, platform independent, accessible from
anywhere, enables
possibility to easily add new application that can be batch
or interactive,
sequential or parallel. Thanks to its open architecture it
can easily integrate
existing or incoming tools - for example supporting grid
operations or enabling
collaborative work. Number of grid applications has already
been integrated with MD
framework.
As a key product of CrossGrid project Migrating Desktop has
proved its usefulness in
everyday work of users’ community. Migrating Desktop was
used in Polish grid project
– Progress and is now used as an integration platform in EU
BalticGrid project.
Interactivity and MPI support is also continually developed
in EU int.eu.grid
project, while tools from MD will become part of Eclipse
based grid toolbox developed
by EU g Eclipse project.

Platform overview
The aim of Migrating Desktop is to provide scientists with a
framework which hides
the details of most of the Grid services and allows working
with grid application in
an easy and transparent way. The graphical user interface
integrates and makes use of
number of middleware and integrates the individual tools
into a single product
providing a complete grid front-end. It uses OSGi
specification as a mechanism for
discovering, integrating, and running modules called
bundles. When MD is launched,
the users can work with environment composed of the set of
bundles. Usually a small
tool is written as a single bundle, whereas a complex tool
has its functionality
split across several bundles. A bundle is the smallest unit
of our platform that can
be developed and delivered separately. Such approach allows
increasing the
functionality in an easy way without the need of
architecture changes. 
Migrating Desktop framework allows users to access
transparently the Grid resources,
run sequential or interactive, batch or MPI applications, to
monitor and visualize
applications, and manage data files. MD provides a front-end
framework for embedding
some of the application mechanisms and interfaces, and
allows the user to have
virtual access to Grid resources from other computational
nodes. 
MD is a front end to Roaming Access Server (RAS), which
intermediates to
communication with different grid middleware and
applications. Roaming Access  Server
offers a well-defined set of web-services that can be used
as an interface for
accessing HPC systems and services (based on various
technologies) in a common and
standardized way. All the communication is based on the web
services technology.

This platform can work with different grid testbeds: based
on LCG 2.7, gLite 3.0, 
Progress 1.0. Due to its open nature it can be extended with
support for other testbeds. 

Applications:
Example application use case: interactive application
(CrossGrid) - Parallel ANN
training application. 
This application is used to train an Artificial Neural
Network (ANN) using simulated
data for the DELPHI experiment. The ANN is trained to
distinguish between signal
(Higgs bosson) events and background event (in the demo the
background used includes
WW and QCD events). The evolution of the training can be
monitored using MD with a
graphics presenting current error, and 4 small graphics that
show the ANN value vs.
an event variable (that can be selected by the user). The
application is compiled
with MPICH-P4 for intracluster use and with MPICH-G2 for
intercluster use. This
application uses the interactive input channel to let the
user make a clean stop of
the training (instead of killing the job), and also the
possibility of resetting the
ANN weights to random values, to avoid local minima. Using
MD, user can change
parameters of this grid application while it is running.

Other application that are already working with MD are: Air
Pollution (crossgrid),
Medical (Grid-based Approach for Virtual Arteries,
crossgrid), Flood Management
Applications (crossgrid), Air Pollution Modeling
(crossgrid), simple Magic
application use-case, 
Planned in the nearest future are: Visualization of Plasma
in Fusion Reactors, GAMESS.

Used technology
Migrating Desktop bases on the Java applet technology. It
can be launched using the
Java Webstart technology or using a web browser with the
appropriate Java Plug-in
included in the Java Runtime Environment (JRE). MD is based
on Swing libraries for
designing graphical user interface, Java CoG Kit version 1.2
is being used as an
interface to Globus (for operation on proxy and GridFTP/FTP)
functionality. Axis
ver.1.2.1 web services client is used for communication with
the Roaming Access
Server. Migrating Desktop follows OSGi Service Platform
specification version 4
(August 2005) and is based on the same plugin engine as
Eclipse platform. Currently
RAS for cooperation with EGEE infrastructure is using LCG2.7
and/or gLite 3.0 platform.

This  application, ported routinely on EGEE, is to provide
first order informations
on seismic source for large Earthquakes occuring worldwide.
These informations are: the centroid, which corresponds to
the location
of the space-time barycenter of the rupture. In this
demonstration some 
examples will be shown and the functionalities of LCG and
gLite used.

AMGA Web Interface is the implementation of the metadata
interface designed by the
ARDA team and it is the official metadata service of the
EGEE gLite middleware. It
provides many interesting features: metadata organization in
a hierarchical
structure, users, groups and ACLs handling with X509
certificates/proxies support,
powerful SQL-like query language, replications. However,
interacting with the AMGA
services is not always user friendly especially for the
non-expert users because the
provided clients are unix command line tools and APIs. So
the need for a simple and
user friendly interface to manage metadata with AMGA arises.
 
We thought to a web interface to achieve access from any
platform: the user just
needs a web browser and a VOMS proxy to be authenticated to
the AMGA server. After a
successful login, he will be able to browse the hierarchy of
AMGA collections, to
inspect their schema and permissions, and to list their
entries. He also has the
ability to create a new collection, to define a metadata
schema for it,
add/edit/delete its entries, and finally to perform queries
against its attribute. In
all the previous operations, the respect of the collection
and entry permissions will
be guaranteed allowing  users to access information for
which he is actually
authorized, thanks to the underlying usage of the AMGA APIs.


In future versions, a module to handle users and groups will
be added. At the moment,
a user needs to own an account in the underlying AMGA
server, and he can only set
permissions and ACLs per collection, granting access to
already existent AMGA groups.

AMGA WI is a J2EE (Java 2 Enterprise Edition) web
application developed with pure
Java technologies (Java Servlet, Java Server Pages, Custom
Tag Libraries). The
application design follows the standard multi-layer web
application architecture
consisting of a data presentation layer, a logic application
layer and a data access
layer. All these layers are built making use of the official
AMGA Java APIs.
 
The data presentation layer consists of all web pages that
make users able to access
all provided features. These pages have a dynamic contents,
according to the data
stored into the AMGA Server backend. The web pages work with
both logic components to
perform data manipulation and with access components to
retrieve and publish data.
 
The logic application layer is made up by all the software
modules that encapsule the
implementation of the provided feautures (metadata handling
and manipulation). Every
AMGA logical entity (collection, entry, attribute,..) is
mapped to a specific
software module. This ensures a very clean and simple
software architecture with an
high degree of cohesion and decoupling. These components
work as services invoked by
the overlying web pages.
 
The data access layer implements all the software components
than ensure the data
extraction from the AMGA server. 
These components work as services invoked by the web pages
and they provide a
mechanism to retrieve data and publish dynamic content.
 
A working beta version will be showed during the demo
session at EGEE 06 conference.

DILIGENT is an ongoing EU IST project whose goal is to
deliver an infrastructure
making possible to define and dynamically create virtual
digital libraries by reusing
available resources. A virtual digital library is a pool of
resources dynamically
aggregated to meet the user requirements where these
resources range from information
sources to services exploiting computing and storage Grid
capabilities. In addition
to such main goal and to prove the viability of the released
infrastructure to meet
their requirements and improve their daily work, two user
communities (ARTE and
ImpECt) belonging to different application contexts have
been selected. As a
consequence, DILIGENT is a project that sits over Grid and
Digital Library (DL)
technologies and it is influenced by requirements arising in
the Cultural Heritage
and Earth Observation domains (the user communities). In
particular, the project
heavily relies on the concept of resources sharing because
the foundational concept
of virtual digital library has been envisaged by elaborating
on and cannot be
implemented without this Grid facility.
By providing to the user communities (i) the capability to
dynamically create DL, and
(ii) to have access to an huge computing and storage
capability, all this with an
acceptable management cost, DILIGENT promises to
revolutionise the way through which
joint research is conducted and propose novel application
scenarios. New kinds of
functionality can be envisaged or improvement of already
existing functionality can
be implemented, the management of new kind of knowledge
becomes feasible, new way to
organise research processes can be implemented. 
In such a scenario EGEE plays a fundamental role. In fact,
being EGEE in charge to
provide a big production quality Grid infrastructure serving
a myriad of
applications, it represents the most attractive provider for
an organised and ready
to use pool of computing and storage facilities.
The Diligent project is currently testing the first
prototype that will be delivered
by the end of September ’06. 
According to the Diligent implementation plan, this version
is not fully-fledged.
Rather it supports the basic DL functionalities required to
satisfy the main user
communities’ requirements.
The aim of this demo is to introduce the current Diligent
prototype through the
presentation of the ImpECt and the ARTE application scenarios. 

The ImpECt scenario (Implementation of Environmental
Conventions) demonstrates the
use of a grid-based digital library for Earth Sciences.

The ImpECt digital library, besides the Diligent basic
services, is currently
providing access to the following information sources and
services:
(1) a collection of processed satellite images showing the
vegetation index;
(2) a collection of digital objects about background
information on MERIS;
(3) the MGVI (MERIS Global Vegetation Index) external service.

The sources together with their metadata are maintained by
the DILIGENT content
management and metadata management, and can be queried by
region, time, and content.
The MGVI service is integrated by means of the DILIGENT
process management. In
addition, searches on external sources (e.g. Google) are
supported using the DILIGENT
search facilities.
Search results can be browsed and used for generating, for a
particular time frame
and location, environmental reports based on a user-defined
template. These
user-defined reports can then be saved and indexed in the
digital library as newly
available information. The user interface for search, result
browsing, and report
generation is realized by means of portlets hosted on a
GridSphere portal. 

The ARTE scenario demonstrates the use of a grid-based
digital library for cultural
heritage domain. Its community, represented by educational
institutions (Schools
and/or Universities) and by the Italian educational
broadcasting network, shares a
set of archives with multimedia content with the aim to
combine them in complex
learning objects, named courses. Once a course is built, it
is stored and made
available to be reused in and adapted for new didactic
contexts. 
In addition to the management of courses, the ARTE DL
provides functionalities to
store, manage, and retrieve all kind of information objects
related to them, such as
images, texts, audio/video recording, etc. 
The current ARTE DL provides access to a number of community
specific information
sources, such as between the others, the "Progetto
Emblemata. 'Con parola brieve e
con figura' Libri antichi di imprese e di emblemi"; “A
Celebration Of Women Writers”;
“Arts And Humanities Data Service”; “Bayerische”; “Gallica”;
“Perseus”; “Emblem
Project Utrecht”; “RAI Medita” collections. 
In order to securely store and make available these set of
copyrighted information
objects on the Diligent Grid infrastructure, the Diligent
content security facilities
have been largely used.

The P-GRADE portal plays more and more important role in the
life of various 
Grid user communities. After several successful demos at the
biggest 
conferences and Grid user forums in Europe, Asia and the US,
the 
representatives of several Grids and Grid based Virtual
Organizations have 
approached us and requested to support their communities by
the Portal. As a 
result, the P-GRADE portal is already the official portal of
the VOCE (Virtual 
Organization Central Europe), HunGrid (Hungarian VO of EGEE)
and the eGrid 
(Economic Grid) VOs of the EGEE Grid. It also provides
service for the users of 
GILDA (the Grid training infrastructure of EGEE), Croatian
Grid and Turkish Grid 
infrastructures. Moreover, the P-GRADE portal is the
official portal of SEE-GRID 
which operates a Grid infrastructure in the South-East
Europe region. Besides 
LCG-2 and gLite based production Grids the portal is
successfully used as 
service for the GT2 based UK National Grid Service (NGS) and
it was also 
successfully connected to the GT4 based Westfocus Grid (UK).
Our latest 
achievement is that the P-GRADE Portal has been connected to
the ARC 
middleware, thus now it is able to execute Grid applications
in the Nordugrid 
too. After a successful demonstration at the
Supercomputing'05 exhibition the 
representatives of the US Open Science Grid and Teragrid
also expressed their 
interest to connect the portal to their Grid. Consequently,
the P-GRADE Portal is 
now connected to both OSG and Teragrid, reaching the users
of many large 
production Grid infrastructures of the World. Moreover,
recently the GIN (Grid 
Interoperation/Interoperability Now) Grid of GGF is
supported by the portal 
enabling the simultaneous access to all of its resources
coming from different 
Grids.

As P-GRADE portal becomes more and more popular among users
we have 
received important feedbacks asking for new features of the
portal. One of 
those requests was the support of parametric studies at the
workflow level. 
The idea of parametric study applications is that the same
workflow should be 
executed with a large number of different input data files.
Moreover, different 
jobs must be fed by different number of files and the portal
should be able to 
automatically generate the cross-product of these input
files and run the 
workflow for each element of this cross-product. Obviously
handling large 
number of workflows and files raises many new problems. Here
we mention 
only some of them just to illustrate the problems:

1. Where to place and how to organize the necessary input files?
2. Where and how to store the output of each execution of
the workflow?
3. How to prevent flooding the Grid and the portal by large
parameter study 
applications?
4. How to specify the parametric study workflows in a way
that simply extends 
the specification of normal workflows?
5. How to manage the large number of workflows by the portal?

The main principles of supporting parametric study
application by P-GRADE 
portal are as follows:

1. Any port of a PS-WF (parametric study workflow) can be
used to feed many 
files to the WF. Such a port is called as PS-port and
distinguished from the 
ordinary input ports both in the UI and in the inner
representation of the WF. 
For each PS-port in a PS-WF there is a unique integer
identifier (an ordering 
number starting from 0) generated by the portal.
2. A PS-port represents a set of input files that are stored
in the same directory 
of a SE (storage element). It is the responsibility of the
user to place these 
input files into the SE before submitting the PS-WF. Such a
directory must not 
store any other files, only the input files belonging to the
associated PS-port. 
3. If there are several PS-ports in a PS-WF, then the portal
RS (run-time 
system) takes care of producing the necessary cross-product
of the input files 
of these PS-ports. 
4. For each element of the cross-product the RS generates an
executable WF 
(e-WF). The internal representation of an e-WF is the same
as the normal WF. 
5. Once the RS generated an e-WF it submits this e-WF in the
same way as 
normal e-WFs are submitted (since they are the same).
6. The number (N) of e-WFs that are generated for parallel
execution is the 
decision of the portal. When a PS-WF is submitted, the
portal RS generates N e-
WFs of the cross product and submit them simultaneously to
the Grid. Once an 
e-WF is completed the portal RS generates the next element
of the cross 
product and the related e-WF and submits it into the Grid.
7. An extra global parameter of a PS-WF is the target output
directory of the 
workflow results. The target output directory must be in a SE.
8. Once an e-WF is completed the portal moves the zipped
result into the 
target output directory. As a result not more than N partial
WF results should 
be stored on the portal simultaneously for one PS-WF. Any
post-processing of 
the results is the task of the user and not of the portal.
9. To avoid the flooding of the Grid and portal by a single
user, one user can 
submit only one PS-WF at a time. The next one can be
submitted if the 
previously submitted PS-WF is completed. Moreover, the
portal administrator 
can set the maximum number of e-WFs that can be
simultaneously generated 
from a single PS-WF as well as the maximum number of jobs
that can be 
submitted by the portal to the Grid.

During the demo of the portal we will demonstrate how the
new PS support 
feature of P-GRADE portal works. We hope that this new
feature will 
significantly increase the usability of the portal and will
open doors for many 
new Grid user communities.

The demo shows two types of browser applications developed
on top of the gLite
metadata catalogue AMGA.
The first one is a generic database GUI which allows an
interactive exploration of
the metadata schema and entries plus the possibility to
issue SQL queries on the
catalogue itself.
The second one is a specialised version developed for the
LHCb experiments. In this
case the system has been tailored to execute the allowed
users' queries. This system
allows usage from other applications (as Ganga, the ATLAS
and LHCb grid user
interface) and via a GUI. This browser has also a role in
allowing seamless migration
from early LHCb metadata prototypes: the system can issue
the same queries on other
backend (XML-RPC Oracle prototype).
Both systems benefit from the main features of AMGA, namely
efficient
access to database backends and flexible security features.

Bioinformatics analysis of data produced by high-throughput
biology, for instance genome projects [1], is one of 
the major challenges for the next years. Some of the
requirements of this analysis are to access up-to-date 
databanks (of sequences, patterns, 3D structures, etc.) and
relevant algorithms (for sequence similarity, multiple 
alignment, pattern scanning, etc.) [2]. Since 1998, we are
developing the NPS@ Web server ([3], Network 
Protein Sequence Analysis), that provides the biologist with
many of the most common resources for protein 
sequence analysis, integrated into a common workflow. These
methods and data can be accessed through simple 
web browsing and HTTP connection, or througth high-level
bioinformatics interface like MPSA program [4] or 
AntheProt [5].
Today, the computing resources available behind the NPS@ Web
portal limit the capabilities of our server, as it is 
the case also for other genomics and proteomics Web portals.
Indeed some methods are very computing-time 
and memory consuming.  Our NPS@ portal is facing an
increasing demand of CPU and disk resources and the 
management of numerous bioinformatics resources (algorithms,
databanks).
NPS@ [3] is providing biologist with a Web form to input
their data (protein sequences) in order to run a BLAST 
analysis against a given protein sequence database. User
pastes his sequence of protein in the corresponding 
field. Then he chooses the database that will be scan with
the query sequence. All the protein databases available 
on NPS@ can be selected through a multi-valued list of the form.
GPS@ grid web portal (Grid Protein Sequence Analysis,
http://gpsa-pbil.ibcp.fr) is the grid release of the NPS@ 
bioinformatics portal. GPS@ hides the mechanisms required
for submitting bioinformatics analyses on the grid 
infrastructure. Selecting the “EGEE” check-box will schedule
the submission of the BLAST on the EGEE grid [6] 
when clicking on the “submit” button. The bioinformatics
algorithms and databases available on GPS@ have been 
distributed and registered on the grid and GPS@ runs its own
EGEE interface to the grid.
First, the job description in the Web form is converted into
a JDL file, that can then be submitted to the workload 
management system of EGEE. The GPS@ sub-process that have
submitted the job, is also checking periodically 
the status of this job by querying the resource broker with
the good commands. All steps are notified to the user 
through the Web page of the submission, indicating the time
and the duration of the current step. When 
achieved, i.e. reaching the “Done” step, the GPS@ automat
downloads the result file from BLAST. Then this raw 
result file in BLAST format is processed and converted into
a HTML page showing, in a colored and graphical way, 
the list of similar protein sequences, and also graph and
pairwise alignments of them. This formatting process is 
directly inherited from the original NPS@ portal, providing
biologists with a well-known interface and way of 
displaying results.
GPS@ portal makes the Bioinformatics job submission easier
on the grid, and provide biologist with the benefit of 
the EGEE grid infrastructure to analyze large biological
dataset: e.g. including several protein secondary structure 
predictions into a multiple alignment, or clustering a
sequence set by analyzing, with BLAST or SSEARCH, each 
sequence against the others, …

Acknowledgements
This work has been funded by GriPPS project (ACI GRID
PPL02-05), EGEE project (EU FP6, ref. INFSO-508833) 
and EMBRACE Network of Excellence (EU FP6, LHSG-CT-2004-512092).

References
[1]	Bernal, A., Ear, U., Kyrpides, N. : Genomes OnLine
Database (GOLD): a monitor of genome projects world-
wide. NAR 29 (2001) 126-127
[2]	G. Perrière, C. Combet, S. Penel, C. Blanchet, J.
Thioulouse, C. Geourjon, J. Grassot, C. Charavay, M. Gouy, L. 
Duret and G. Deléage, Integrated databanks access and
sequence/structure analysis services at the PBIL. Nucleic 
Acids Res., 31:3393-3399, 2003.
[3]	Combet, C., Blanchet, C., Geourjon, C. et Deléage, G. :
NPS@: Network Protein Sequence Analysis. Tibs, 25 
(2000) 147-150.
[4]	Blanchet, C., Combet, C., Geourjon, C. et Deléage, G. :
MPSA: Integrated System for Multiple Protein 
Sequence Analysis with client/server capabilities.
Bioinformatics, 16 (2000) 286-287.
[5]	Deleage, G, Combet, C, Blanchet, C, Geourjon, C. :
ANTHEPROT: an integrated protein sequence analysis 
software with client/server capabilities. Comput Biol Med.,
31 (2001) 259-267
[6]	EGEE – Enabling Grid for E-science in Europe;
http://www.eu-egee.org

Traditional developments in Grid technologies have
concentrated on providing batch
access to distributed computational and storage resources.
The requirements to
access, control, and acquire data from widely networked
distributed instruments
trigger the need to include a variety of new components. For
instance, scientific
equipment like sensors and probes are a need in nowadays
Grid infrastructures. This,
in turn, raises the need for supporting real-time operations
and interactive work,
thus opening a new frontier of research and development in
this field. 
The GridCC Project, launched in September 2004 by the
European Union, addresses these
issues. The goal of GridCC is to exploit Grid opportunities
for secure and
collaborative work of distributed teams to remotely operate
and monitor scientific
equipment. In addition, GridCC will allow to exploit the
Grid’s massive memory and
computing resources for storing and processing data
generated by this kind of equipment. 
In this talk we present first the status of the GridCC
Project, focusing then on the
real applications that have been equipped with our
middleware. We have three main
running use cases, from the run control of a high energy
physics experiments, to the
remote control and monitoring of a grid of small power
generators and, finally, to
the far remote operation of a particle accelerator. Other
applications that have
adopted our approach will be also presented; their field
ranges from meteorology, to
education, to the control of the territory (geo-hazard) and
to the remote control and
monitoring operations of telecommunication measurement
equipment.  
Lastly, the integration with the gLite components will be
highlighted, showing how
the services’ orchestration through a workflow engine has
been introduced. Our
approach, based ontwo levels (namely, strict and loose) of
guarantees to support and
monitor the real-time and interactive requirements will be
also shown.

The EGEE grid infrastructure has grown over the 30 
months of EGEE and EGEE-II from around 40 sites to 
close to 200.  It is now in daily use on a significant 
scale, and is acting as the primary source of computing 
and storage for several application communities.   
Although this growth has been impressive, with the 
LHC coming on-line a year from now the scale of 
resources and workload is expected to increase 
dramatically.  This is an appropriate time to review the 
progress that has been made in building this large 
production grid facility, its relationship with other  
production grids, to summarize the outstanding issues, 
and to look forward to the problems and issues we may 
be facing in the future - both in the short term and on 
the slightly longer timescale.

Over the past decade we have worked closely with 
Scientists - and specifically Life Sciences -  to deliver 
systems and middleware to help solve their data 
management and integration problems. Its has been, 
and continues to be, an interesting learning experience. 
Most recently our myGrid project - which has produced 
the Taverna Workflow Workbench - has successfully 
bridged to the Bioinformatics community in that the
Scientists have not only driven the developments but 
they have also adopted the technology that we have 
produced to do Science. So why did we succeed this 
time and how could we do better?  What were the 
tipping points? How did we create (or not) the 
environment for adoption? What are the technical, 
social and political imperatives for true engagement
with applications? Why are Life Scientists from Venus 
and Computer Scientists from Mars?

An overview of the status of the NA4 activity followed by a
description of the major challenges for the activity.

Status of HEP application sector.

Summary of biomedical application sector.

Summary of Earth Science application sector.

Status of the Fusion application sector.

Summary of computational chemistry application sector.

Summary of astrophysics and astroparticle physics sector.

Status of the GILDA t-Infrastructure.

Open discussion concerning the points raised in the summary
talks or other concern or suggestions from NA4 participants.

1 presentation per each country involved
2-3 minutes each

Presentation and discussion about the Sustainable Grid
Infrastructure/Initiative and the conditions and
requirements in the CE region

results of the Service Challenge 4
Cyfronet

The evolution of YAIM

A short introduction to the session, explaining why
communication is a key issue for EGEE and other projects.

This talk, given by a professional writer and ex-journalist
working on issues surrounding the Grid, is intended to make
it easier for members of the community to deal with the
press. By understanding how the press operates, delegates
should find it easier to approach the media with stories,
and how to react when the media approaches them.

This session will feature a panel discussion with members of
the dissemination and training activities within the
project, grid journalists and professional writers on issues
relating to the media. The members will answer questions
from the floor, or questions can be submitted in advance to
owen.appleton@cern.ch with ‘PR Question’ in the title field.

The first part of the presentation will introduce QA 
standards such as :
- Service Management (ITIL, ISO/IEC 20000-1/-2:2005)
- CMMi
- Quality Management ISO 9001,
- Security Management ISO 2700
The second part will present Serono implementation 
choices and benefits

The GÉANT network is a pan-European backbone which 
connects Europe's national research and education 
networks. EGEE is built on GEANT network.
CSSI as industrial contractor is responsible for the 
operation management of the Network Operation 
Center (NOC).
The presentation will highlight the benefits of 
implementing ITIL for GEANT NOC.

An overview of the history of the User Information 
Group in EGEE, its purpose and its limitations. A 
summary of progress made so far in EGEE-II, and an 
outline of future plans for the activities of the group.

This contribution will describe progress to date on the 
first group of user scenarios which will comprise the 
output of the user Information group in EGEE-II. These 
are intended to provide easy, user-friendly access to 
user information covering EGEE operations from 
beginner to advanced user level.

All Related Projects will be presented so as to give
everybody involved a bird's eye view of the whole EGEE and
Related Projects ecosystem.

Key EGEE Activities will be presented to the Related
Projects participants by senior EGEE activity members. This
will help orient the Related Projects to the EGEE
structures, what is offered, and by whom.

An opportunity to Related Projects participants to discuss
with EGEE members from key activities. The purpose is to
give everybody the ability to raise any issues and get
answers to their questions having both Related Projects and
EGEE on board.

Update on EGEE MW security - this is covered in more detail
at the JRA1 sessions at the conference.

How is it working, what are the outstanding issues?

Clarify the stratgey, status, what is missing?
Does this look like SLAs?

What about the rest of the metrics programme - we 
need people to work on that.

Presentation of the process that has been agreed in 
the PEB/PMB.  What is expected from the sites now?

The presentation will focus on lessons learnt and 
experience sharing for building IT services based on 
ITIL and Sun Operations Management Capabilities 
Model (OMCM)

The presentation will cover:
- QA certification in Enginneering, reasons and 
objectives,
- How Engineering applied QA CMMi certification to its 
complex organisational model (a group of 13th 
companies, involved in several markets from bank and 
finance to utility and defense, with several distinct 
technologies).
- the concrete process followed in getting the 
certification.