Governing Energy Awareness in Cloud Data Center

The emergence of Cloud Computing has made the feasibility of providing computing resources as services over the internet. These computing resources have been the major contributors to massive energy consumption, due to the presence of high speed computing devices. Cloud data centers consume tremendous energy in order to serve unpredictable, random requests from millions of consumers worldwide. Addressing and curtailing this energy consumption is associated with finding an energy efficient resource allocation mechanism in cloud data center that tries to overcome the main issue related with the need to save energy conservation for future use. Energy efficiency of a cloud data center can be measured in terms of Power Usage Effectiveness (PUE) and Dynamic Range. Software Defined Networking (SDN) primarily aids in separating the control plane from data plane in cloud data center networks. The need to adapt to fully green cloud data center networks, not only reduces wastes to keep environment eco-friendly, but is also economically beneficial in reducing the operating costs. An approach to reduce the massive energy consumption is to make use of load balancing techniques like Weighted First-cum-First-Served helps in avoiding overheating and overloading of servers, by evenly balancing the workload across all the servers in the data center, hence reducing the amount of energy consumed physical machines at run time, in such a way that, Weighted First-cum-First-Served (WFCFS) is chosen as the optimal energy aware load balancing solution, as it improves the performance and achieves minimum power consumption, minimum cost, minimum overall time taken, in comparison with other load balancers, thereby saves energy consumption to a greater extent. The central objective of this work is dedicated to focus on monitoring energy awareness in cloud data center with the aid of energy efficient resource allocation strategy to curtail the tremendous energy consumption and thereby achieve Green cloud environments.