A green network-aware VMs placement mechanism

Data centers power consumption corresponds to near 2% of the total world wide power consumption, with constantly increasing greenhouse effect and CO₂ footprints. Virtualization techniques improve the efficiency of data centers infrastructure sharing a same physical hardware among several Virtual Machines (VMs). An efficient VM placement can minimize even further the hardware and energy needs. In contrast to existing VM placement algorithms that usually focus on a single resource or assumes that resources demands are deterministic, this paper proposes and compares four energy-aware algorithms that consider multiple stochastic resources, including network bandwidth. We first formulate the problem as a multi objective optimization problem with stochastic resources and we present two algorithms based on this approach. We also formulate the problem as an evolutionary computation problem and we present two algorithms based on this approach. The objective is a joint strategy: minimize the required hardware to maximize the allocated VMs satisfying the resource requirements. Through simulations, we compare our algorithms using real VMs workloads from the PlanetLab project and showed the significant improvements on power consumption and network utilization. In average, the algorithms reduce power consumption by 87.90% and the network utilization by 9.94%.