Abstract
Load balancing is an efficient solution that distributes excess workload evenly to all nodes in cloud environment. The Load balancing model is used for the public cloud having numerous nodes in different geographic locations. The model divides public cloud into several cloud partitions. When partition status becomes overloaded, cloud partitioning is repeated. It reduces the working efficiency and expected response time of the system. To overcome this issue we propose a novel load balancing strategy for overloaded cloud partition. The overloaded load balancing strategy maintains two queues at overloaded condition. Priority queue is used when the cloud partition status is idle and normal and non priority queue is used when partition status is overloaded. At overloaded condition an overloaded partition scheduling algorithm is used for the allocation of jobs to Non priority queue. When a priory job ends, then one of the jobs in Non priority queue moves to priority queue based on arrival time and processing power required
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