A Baye's Theorem Based Node Selection for Load Balancing in Cloud Environment

Cloud computing is a popular computing model as it renders service to large number of users request on the fly and has lead to the proliferation of large number of cloud users. This has lead to the overloaded nodes in the cloud environment along with the problem of load imbalance among the cloud servers and thereby impacts the performance. Hence, in this paper a heuristic Baye's theorem approach is considered along with clustering to identify the optimal node for load balancing. Experiments using the proposed approach are carried out on cloudsim simulator and are compared with the existing approach. Results demonstrates that task deployment performed using this approach has improved performance in terms of utilization and throughput when compared to the existing approaches.