Speaker
T. Coviello
(DEE – POLITECNICO DI BARI, V. ORABONA, 4, 70125 – BARI,ITALY)
Description
Grid computing is a large scale geographically distributed and
heterogeneous system that provides a common platform for running
different grid enabled applications. As each application has
different characteristics and requirements, it is a difficult
task to develop a scheduling strategy able to achieve optimal
performance because application-specific and dynamic system status
have to be taken into account.
Moreover it may be possible to obtain optimal performance for
multiple application simultaneously using a single scheduler. Hence
in a lot of cases the application scheduling strategy is assigned to
an expert application user who provides a ranking criterion for
selecting the best computational element on a set of
available resources. Such criteria are based on user perception of
system capabilities and knowledge about the features and requirements
of his application.
In this paper an intelligent mechanism has been both implemented and
evaluated to select the best computational resource in a grid
environment from the application viewpoint.
A neural network based system has been used to capture automatically
the knowledge of a grid application expert user. The system
scalability problem is also tackled and a preliminary solution based
on sorting algorithm is discussed. The aim is to allow a
common grid application user to benefit of this expertise.
Primary authors
G. PISCITELLI
M. Castellano
(DEE – POLITECNICO DI BARI, V. ORABONA, 4, 70125 – BARI,ITALY)
T. Coviello
(DEE – POLITECNICO DI BARI, V. ORABONA, 4, 70125 – BARI,ITALY)
