consumption in cloud data centers and we developed a new VM selection algorithm. A Simulation was performed under a complex scenario, and the results from the simulation are presented in this paper. Finally, we have demonstrated an analysis on obtained simulation results. The final results have shown that our proposed algorithm is more energy efficient compared to the existing one.

Related Work {#Rela_wo}
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The promising model for utility computing was proposed by \[2,3\] which delivers various cloud services. Utility computing provides computation, storage, data access, software, and other software services. The increasing demand of cloud computing power consumption for data centers and cooling system have raised tremendously. However, reducing power consumption of cloud computing infrastructures is a challenging research issue.\
Power management of virtualized data center in terms of energy-aware had been studied by Nathuji and Schwan \[4\]. Cloud computing resource provision is unpredictable and workload has varied over time. Random online algorithms and non-deterministic online algorithms normally improve the quality in a similar scenario compared to deterministic algorithms, as discussed by Ben-David et al. \[5\]. Algorithm depends on the input provided from distributed model and cannot be modeled using a plain statistical distribution \[6,7\] due to the complexity 