An Energy Efficient Virtual Machine Placement Algorithm Based on Graph Partitioning in Cloud Data Center

Energy efficiency is a hot topic in the research of virtual machine placement (VMP). As the network equipment energy consumption problem has become increasingly prominent, many studies through resource aggregation to save energy, which can easily lead to resource competition and SLA violations. In this paper, we present a virtual machine placement algorithm based on graph partitioning (GPVMP) to achieve energy optimization. For the virtual machine (VM) group submitted by the user, we reconstruct the VM associated graph according to the traffic and load correlation between VMs, and partition the graph using the improved multilevel k-way partitioning algorithm. Combined with the data center topology, the two-layer mapping relationship of VMs and physical machines (PMs) is determined by extending PM clusters. The experimental results show that our proposed algorithm can guarantee better resource utilization, control SLA violation and offer a significant savings of energy compared with other related algorithms.