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A Load Balanced Greening Approach for Proficient Resource Allocation with Cloud Partitioning

R.Divya, S. Premkumar deepak

Cloud computing is mainly used in load balancing technique. It has improved performance and user satisfaction. Cloud providing users with new type of services. Here different type of strategies can be used. Previously they have used ANT colony optimization and Game theory method. Here job arrival pattern is not predictable. In this method not flexible and also not efficient. Load balancing schemes depending on either static or dynamic. Thus, this model divides the public cloud into several cloud partitions. When the environment is very large and complex, these divisions simplify the load balancing. The cloud has a main controller that chooses the suitable partitions for arriving jobs while the balancer for each cloud partition chooses the best load balancing strategy. The load balancing strategy is based on the cloud partitioning concept. After creating the cloud partitions, the load balancing then starts. When a job arrives at the system, with the main controller deciding which cloud partition should receive the job. The partition load balancer then decides how to assign the jobs to the nodes. When the load status of a cloud partition is normal, this partitioning can be accomplished locally. If the cloud partition load status is not normal, this job should be transferred to another partition. When the node is idle, the data will be directly shared to another node inside the partition by using green computing concept. Normally, cloud computing is a cost per usage. When transfer the image to the cloud, the size of the image can be reduced by the decomposition technique. This whole project mainly deals with reducing data size and cloud space.