This paper aims to explore the opportunities in porting a highthroughput Grid computing middleware to a high-performance service oriented environment. It exposes the limitations of the Grid computing middleware when operating in such a performance sensitive environment and presents ways of overcoming these limitations. We focus on exploiting the heterogeneity of the Grid resources to meet the performance requirements of services and present several approaches of work distribution to deal with this heterogeneity. We present a heuristic for finding the optimum decomposition of work and present algorithms for each of the approaches which we evaluate on a real live testbed. The results validate the heuristic and compare the performance of the different workload distribution strategies. Our results indicate that a significant improvement in performance can be achieved by making the Grid computing middleware aware of the heterogeneity in the underlying infrastructure. The results also provide some useful insights into deciding a work distribution policy depending on the status of the Grid computing environment.
Trivedi, Rahul; Chandra, Abhishek; Weissman, Jon.
Heterogeneity-Aware Workload Distribution in Donation Based Grids.
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