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Hybrid predictive approach for replica replacement in data grid

Data replication in data grid increases the availability of data and reduces the total execution time of the grid job. Replica replacement algorithm plays a vital role when storage space is limited. It is this algorithm that decides which replica should be replaced for the new one. The binomial prediction, Least Frequently Used (LFU) and Least Recently Used (LRU) replica replacement algorithms are well known in the grid environment. The proposed Hybrid Predictive (HP) approach utilizes the advantages of all these algorithms on replica replacement. The HP is simulated in the OptorSim on a common platform. Mean Job Execution Time (MJET), Hit Rate (HR), Effective Network Usage (ENU), Computational Element Usage (CEU) are considered as performance metrics. The results are experimentally compared with Binomial based Replica Replacement algorithm, LFU and LRU.