Energy Efficient Mechanism for Green Computing in Wireless Storage Area Networks

Core of data-centric computing implies faster analysis and figures out immediate solution workaround for complicated problems. Scaling down energy expenditure is an important factor in data-centric IT Resources. This paper proposes the concept which enhances the utilization of Green computing technique in servers and switches in order to reduce the overall power consumption in wireless storage area network. In this proposed system the linear power model and low power blade model were used to reduce energy consumption in central processing unit and calculation for the number of individual tasks carried out by the user and depending upon the user's requirement server is selected. The remaining servers are set to power management schemes such us voltage scaling, frequency scaling and dynamic shutdown techniques. In particular, our approach relies on consolidating services dynamically onto a subset of the available servers and temporarily shutting down servers in order to conserve energy. Our experimental simulations revealed that there is an increasing percentage of energy savings in DNS mode up to 54% energy savings.