A two phased service oriented Broker for replica selection in data grids
Future Generation Computer Systems
Dynamic replica placement and selection strategies in data grids- A comprehensive survey
Journal of Parallel and Distributed Computing
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Genetic algorithms are becoming increasingly valuable in solving large-scale, realistic, difficult problems, and selecting replica with multiple selection criteria - availability, security and time- is one of these problems. In this paper, a rank based elitist clustering Genetic Algorithm is proposed named RRWSGA, which alleviates the problem of being trapped in local clustering centroids using k-mean. Simulation results show that the proposed RRWSGA, outperforms k-mean by 9%. Much better performance of RRWSGA is observed.