A Review of Energy Efficient Optimization Techniques for VM Placement in Cloud Data Centers

Cloud computing is the evolving field with new generation technologies to provide state-of-the-art services to customers and organizations situated worldwide. The data centers in the network of servers are the backbone of the Cloud computing environment with a huge capacity of processing and data storage. Nowadays, data centers are in the limelight for consuming the large amount of energy to support cloud computing services throughout the world. Although several techniques are implemented till now to minimize the energy wastage in data centers, still optimization of designed policies is required. Virtualization approach is used to consolidate the server workload for utilization of computing resources. During the consolidation process, different Virtual Machine placement techniques can be applied with evolutionary algorithms to reduce the energy consumption of servers. In this paper, the critical review of evolutionary algorithms (Genetic Algorithm, Ant Colony Optimization, and Particle Swarm Optimization) used with placement approaches for energy optimization, is conducted to identify the improvement scope and future research directions in this area.