IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 11, 2015 | ISSN (online): 2321-0613

Cloud computing has revolutionized the information technology industry by enabling elastic on demand provisioning of computing resources. Cloud data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. The goal is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. One method to improve the utilization of data center resources, which has been shown to be efficient, is dynamic consolidation of Virtual Machines (VMs). Energy consumption is reduced by dynamically deactivating and reactivating physical nodes to meet the current resource demand. We propose an optimal offline algorithm for the host overload detection problem, as well as a Markov chain model that allows a derivation of an optimal randomized Control policy under an explicitly specified QoS goal for any known stationary Workload.. Here going to implement by using CloudSim Tool Kit by creating Data Center, hosts, Broker, Virtual Machine etc.