Speaker
Nuno Filipe De Sousa Santos
(Universidade de Coimbra)
Description
1. Introduction
Metadata Services play a vital role on Data Grids, primarily as a means of
describing and discovering data stored on files but also as a simplified database
service. They must, therefore, be accessible to the entire Grid, comprising several
thousands of users spread across hundreds of Grid sites geographically distributed.
This means they must scale with the number of users, with the amount of data stored
and also with geographical distribution, since users in remote locations should have
low-latency access to the service. Metadata Services must also be fault-tolerant to
ensure high-availability.
To satisfy such requirements, Metadata Services must offer flexible replication and
distribution mechanisms especially designed for the Grid environment. They must cope
with the heterogeneity and dynamism of a Grid, as well as the typical workloads.
To address these requirements, we are building replication and federation mechanisms
into AMGA, the gLite Metadata catalogue. These mechanisms work at the middleware
level, providing database independent replication, especially suited for
heterogeneous Grids. We use asynchronous replication for scalability on wide-area
networks and improved fault-tolerance. Updates are supported on the primary copy,
with replicas being read-only. For flexibility, AMGA supports partial replication
and federation of independent catalogues, allowing applications to tailor the
replication mechanisms to their specific needs.
2. Use Cases
Replication on AMGA is designed to cover a broad range of usage scenarios that are
typical of the main user communities of EGEE.
High Energy Physics (HEP) applications are characterised by large amounts of
read-only metadata, produced on a single location and accessed by hundreds of
physicists spread across many remote sites. By using AMGA replication mechanisms,
remote Grid sites can create local replicas of the metadata they require,
either of the whole metadata tree or of parts of it. Users at remote sites
will experience a much improved performance by accessing a local replica.
For Biomed applications the main concern with metadata is ensuring its security, as
it often contains sensitive information about patients that must be protected from
unauthorised users. This task is made more difficult by the existence of many grid
sites producing metadata, that is, the different hospitals and laboratories where it
is generated. Creating copies on remote sites increases the security risk and,
therefore, should be avoided. AMGA replication allows the federation of these Grids
sites into a single virtual distributed metadata catalogue. Data is kept securely on
the site it was generated, but users can access it transparently from any AMGA
instance, which discovers where the data is located and redirects the request to
that AMGA instance, where it will be executed after the user credentials have been
validated.
We believe that partial replication and federation as they are being implemented in
AMGA provides the necessary building blocks for the distribution needs of many other
applications, while at the same time offering scalability and fault-tolerance.
3. Current Status and Future Work
We have implemented a prototype of the replication mechanisms of AMGA, which is
currently undergoing internal testing. Soon we will be ready to start working with
the interested communities, with the goal of better evaluating our ideas and of
obtaining user feedback to guide us through further development of the replication
mechanisms.
A clear user requirement that we will study is the dependability of the system,
including mechanisms for detecting failures of replicas and for recovering from
those failures. If the failure is on a replica, clients should be redirected
transparently to a different replica. If the failure is on the primary copy, then
the remaining replicas should elect a new primary copy among themselves. All these
mechanisms need an underlying discovery system to allow replicas to locate and query
each other, as well as mechanisms for running distributed algorithms among the nodes
of the system.
Author
Nuno Filipe De Sousa Santos
(Universidade de Coimbra)
Co-author
Birger Koblitz
(CERN)
