Migration of Virtual Machines is one of the efficient ways to manage resources in a Cloud Data Centre, dynamically, and reduce various runtime costs. But, sometimes, rigorous movement of virtual machines from over-utilized or under-utilized physical machines, results in performance degradation and service level agreement violation. Hence, it must be done carefully. A new virtual machine selection policy has been proposed in this paper which uses the concept of least deviation and resource satisfaction aspect for selection of a virtual machine which need to be migrated from overloaded servers in a cloud data centre. The proposed policy has been evaluated via extensive simulations by performing experiments on real workload traces from PlanetLab. The performance of proposed policy has been compared with already existing traditional policies for selection of virtual machine from over-utilized or under-utilized machines like Minimum Migration Time (MMT), Minimum Utilization (MU) and Random Selection (RS) available in CloudSim toolkit. The results show that the proposed policy outperforms the above mentioned policies on the basis of parameters like Power Consumption, SLA violation, No. of migrations, Energy Violation Metric.

Cloud Data Centre, VM Selection, Energy Efficiency, Resource Satisfaction Aspect, QoS, SLAs, VM Consolidation and Redistribution

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