Dear All,

I am pleased to inform you that we have formally released the Gridbus
Broker that supports Computational and data Grid brokering and
applications scheduling on Global Grids. This broker has been used in
demonstration a number of applications as part of our HPC Challenge -
http://www.gridbus.org/sc2003/ - demonstration at SC 20003 conference in
Phoenix, USA. A technical report abstract can be found below and full
report can be downloaded from:
http://www.gridbus.org/papers/gridbusbroker.pdf
The broker code released in GPL license can be downloaded from:
http://www.gridbus.org/broker/

Cheers
Raj

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Title: A Grid Service Broker for Scheduling Distributed Data-Oriented
Applications on Global Grids
Authors: Srikumar Venugopal, Rajkumar Buyya and Lyle Winton
Comments: 15 pages, 11 figures, 1 table
Report-no: Technical Report, GRIDS-TR-2004-1, Grid Computing and
Distributed Systems Laboratory, University of Melbourne, Australia,
February 2004
Subj-class: Distributed, Parallel, and Cluster Computing
ACM-class: C.1.4
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The next generation of scientific experiments and studies, popularly
called as e-Science, is carried out by large collaborations of
researchers distributed around the world engaged in analysis of huge
collections of data generated by scientific instruments. Grid computing
has emerged as an enabler for e-Science as it permits the creation of
virtual organizations that bring together communities with common
objectives. Within a community, data collections are stored or
replicated on distributed resources to enhance storage capability or
efficiency of access. In such an environment, scientists need to have
the ability to carry out their studies by transparently accessing
distributed data and computational resources. In this paper, we propose
and develop a Grid broker that mediates access to distributed resources
by (a) discovering suitable data sources for a given analysis scenario,
(b) suitable computational resources, (c) optimally mapping analysis
jobs to resources, (d) deploying and monitoring job execution on
selected resources, (e) accessing data from local or remote data source
during job execution and (f) collating and presenting results. The
broker supports a declarative and dynamic parametric programming
model for creating grid applications. We have used this model in
grid-enabling a high energy physics analysis application (Belle Analysis
Software Framework). The broker has been used in deploying Belle
experiment data analysis jobs on a grid testbed, called Belle Analysis
Data Grid, having resources distributed across Australia interconnected
through GrangeNet.
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