Dynamic Multi-Objective Virtual Machine Placement in Cloud Data Centers

Minimizing the resource wastage reduces the energy cost of operating a data center, but may lead to a considerably high resource overcommitment affecting the Quality of Service (QoS) of the applications. Determining the effective tradeoff between resource wastage and overcommitment is a challenging task in virtualized data centers and depends on how virtual machines are allocated to physical ones. We propose in this paper a multi-objective approach to dynamic placement of VMs exploiting live migration mechanisms, optimizing resource wastage, overcommitment ratio and migration cost simultaneously. The optimization algorithm is based on a novel evolutionary meta-heuristic using an island population model underneath. Simulation results on real-world traces demonstrate that our approach outperforms other related approaches by reducing up to 57% migrations energy consumption while achieving different energy and QoS goals.