Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2003-02-13
Computer Science
Distributed, Parallel, and Cluster Computing
Technical Report, Grid Computing and Distributed Systems (GRIDS) Lab, Dept. of Computer Science and Software Engineering, The
Scientific paper
The lack of computational power within an organization for analyzing scientific data, and the distribution of knowledge (by scientists) and technologies (advanced scientific devices) are two major problems commonly observed in scientific disciplines. One such scientific discipline is brain science. The analysis of brain activity data gathered from the MEG (Magnetoencephalography) instrument is an important research topic in medical science since it helps doctors in identifying symptoms of diseases. The data needs to be analyzed exhaustively to efficiently diagnose and analyze brain functions and requires access to large-scale computational resources. The potential platform for solving such resource intensive applications is the Grid. This paper describes a MEG data analysis system developed by us, leveraging Grid technologies, primarily Nimrod-G, Gridbus, and Globus. This paper explains the application of economy-based grid scheduling algorithms to the problem domain for on-demand processing of analysis jobs.
Abramson David
Buyya Rajkumar
Daté S.
Mizuno-Matsumoto Y.
Venugopal Srikumar
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