Abstract

Grid computing is some sort of distributed computing which shares the resources, processor and network in the organization or between the organizations for accomplish task. It involves huge amounts of computational task which require resource sharing across multiple computing domains. Resource sharing needs an optimal algorithm; to enhance the performance we should focus on how to increase the global throughput of computational grid. Load balancing in grid which distributes the workloads across various computing nodes to achieve optimal resource utilization, reduce latency, maximize throughput and to avoid any node by overload and under load. Several existing load balancing methods and techniques only interested in distributed systems those are having interconnection between homogeneous resources and speedy networks, but in Grid computing, these methods and techniques are not feasible due the nature of grid computing environment like heterogeneity, scalability and resource selection characteristics. To consider the above problem we need to develop such an algorithm which optimally balances the loads between heterogeneous nodes. It is based on tree structure where load is managed at different levels such as neighbor-based and cluster based load balancing algorithms which reduces complexity can and less number of nodes required for communication during load balancing.KeywordsLoad BalancingHeterogeneousHomogenousResource selectionstatic Load BalancingDynamic Load BalancingExecution timeprocessor capabilitycommunication delaylatencyGridsim

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