In recent years, load balancing is the challenging task which affects the performance in allotting the resources on homogeneous and heterogeneous cluster computing environment. This research proposes an enhancement in ACCS (Adaptively Circulates job among all servers by taking account of both Client activity and System load) policies by incorporating Map Reduce to overcome the problem in balancing the workload for resources. This technique provides simplicity and flexibility for data partitioning, localization and processing jobs as indicated by their present sizes and ranks the servers based on their loads by giving high priority to the smaller jobs. Map Reduce emphasizes more on high throughput of data on low-latency of job execution in a cluster to accomplish huge execution advantages. Trace driven simulations demonstrate the viability and robustness of Map Reduce under numerous different situations.

Load Balancing, Map Reduce, Web Server Clusters, AdaptLoad, ACCS

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