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Scientific applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific applications than we could ever achieve in a single compute resource.In this paper, we...
The Gridbus workflow management system (GWMS) is designed to execute scientific applications, expressed in the form of workflows, onto Grid and Cloud resources. With the help of this system, we demonstrate a computational and data-intensive Image Registration (IR) workflow for functional Magnetic Resonance Imaging (fMRI) applications on Clouds and global Grids. We also present a demonstration of the...
Selection of resources for execution of scientific workflows in data grids becomes challenging with the exponential growth of files as a result of the distribution of scientific experiments around the world. With more runs of these experiments, huge number of data-files produced can be made available from numerous resources. There is lack of work in optimal selection of data-hosts and compute resources...
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