A Deadline and Budget Constrained Scheduling Algorithm for eScience Applications on Data Grids


In this paper, we present an algorithm for scheduling of distributed data intensive Bag-of-Task applications on Data Grids that have costs associated with requesting, transferring and processing datasets. The algorithm takes into account the explosion of choices that result due to a job requiring multiple datasets from multiple data sources. The algorithm builds a resource set for a job that minimizes the cost or time depending on the user's preferences and deadline and budget constraints. We evaluate the algorithm on a Data Grid testbed and present the results

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oaioai:CiteSeerX.psu:10.1...Last time updated on 10/22/2014

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