Energy Saving Heuristics for Optimization of Cloud Data Center

Abstract

In the current scenario the demand for high performance computing system increases day by day to achieve maximum computation in minimum time. Rapid growth of Internet or Internet based services, increased the interest in network based computing or on-demand computing systems like cloud computing system. High computing servers are being deployed in large quantity for cloud computing in form of data Centers through which many different services on internet are provide to the cloud users in a very smooth and efficient manner. A large distributed system is described as a data center that includes a huge quantity of computing servers connected by an efficient network. So the consumption of energy in such data centers is enormously very high. Not only the maintenance of the data centers are too exorbitant, but also socially very harmful. High vitality costs and immense carbon footprints are brought in these data centers because the servers needed a substantial amount of electricity for their computation as well as for their cooling. As cost of energy increases and availability decreases, focus should be shifted towards the optimization of data centre servers for best performance alone with the policies of less energy consumption to justify the level of service performance with social impact. So in this paper we proposed energy aware consolidation technique for cloud data centers based on prediction of future client's requests to increase the utilization of computing servers as per request of users/clients which associated some demand of cloud resources for maintain the power consumption in cloud.