Multi-Objective Optimization of Energy Aware Virtual Machine Placement in Cloud Data Center

Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints environment. Hence, there should be focus on optimal assignment Virtual Machines (VM) Physical (PM) ensure the efficiency service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed improve minimize Service Level Agreement (SLA) violation Environment. idea MOPSO is extended three distinct features such as Largest Processing Time (LPT) rule applied load balancing across which leads saving Environment; Epsilon Fuzzy Dominance used select solutions near front improves diversity solutions; Discrete PSO along strategy algorithm help provide better convergence than existing approaches. produced results other GA heuristics-based approach.