An Energy-Aware Virtual Machine Scheduling Method for Cloudlets in Wireless Metropolitan Area Networks

Abstract

Currently, mobile applications, such as interactive gaming, virtual reality, and natural language processing, are becoming more computational intensive, but the computing capacity of mobile devices is limited. An effective way to solve this problem is offloading the tasks to nearby cloudlets, which are some small mobile data centers deployed in wireless metropolitan area network (WMAN). and consume a large amount of energy. Excessive energy consumption brings about some negative effects, including increased carbon dioxide emissions, aggravating the greenhouse effect, etc. In view of this challenge, we propose an energy-aware virtual machine (VM) scheduling method for cloudlets in WMAN. Technically, an optimization model is designed to formalize our problem. Then, based on VM Live Migration Technology, a corresponding energy saving VM scheduling method abbreviated as MFEA is proposed to determine which VMs should be migrated and where they should be migrated. Finally, experimental data demonstrate that the proposed method is effective.