Research Area:  Cloud Computing

Abstract:

In this paper, we developed a dynamic energy-efficient virtual machine (VM) migration and consolidation algorithm based on a multi-resource energy-efficient model. It can minimize energy consumption with Quality of Service guarantee. In our algorithm, we designed a method of double threshold with multi-resource utilization to trigger the migration of VMs. The Modified Particle Swarm Optimization method is introduced into the consolidation of VMs to avoid falling into local optima which is a common defect in traditional heuristic algorithms. Comparing with the popular traditional heuristic algorithm Modified Best Fit Decrease, our algorithm reduced the number of active physical nodes and the amount of VMs migrations. It shows better energy efficiency in data center for cloud computing.

Keywords:  

Author(s) Name:   Hongjian Li, Guofeng Zhu, Chengyuan Cui, Hong Tang, Yusheng Dou & Chen He

Publisher name:  Springer

DOI:  10.1007/s00607-015-0467-4

Volume Information:  volume 98, pages 303–317 (2016)

Paper Link:   https://link.springer.com/article/10.1007/s00607-015-0467-4