Minimizing Power Consumption and Temperature in CloudComputing

Cloud computing resources are utilized in forms of different virtual machines that provide largescale computation for complicated tasks.The allocation process of virtual machines on physical machines is a critical portion of cloud computing trends.Efficient allocation of the virtual machines on available physical servers is necessary to exploit the high-performance resource utilization and improving power efficiency.In this paper, virtual machine allocation problem is handled by particle swarm optimization with fuzzy multi-objective method.The main goal of the proposed method is to efficiently obtain a near-optimal solution that minimizes power consumption, total processing resource wastage and the peak temperature among the servers.The proposed method has been compared with well-known algorithms for virtual machine allocation problem existed in the literature.The comparison results prove that the proposed algorithm significantly outperforms the compared methods on the basis of power consumption, processing resource wastage and temperature metrics.