Multi-objective virtual machine selection for migrating in virtualized data centers

Authors:
Aibo Song;Wei Fan;Wei Wang;Junzhou Luo;Yuchang Mo
Affiliations:
School of Computer Science and Engineering, Southeast University, Nanjing, P.R. China;School of Computer Science and Engineering, Southeast University, Nanjing, P.R. China;School of Computer Science and Engineering, Southeast University, Nanjing, P.R. China;School of Computer Science and Engineering, Southeast University, Nanjing, P.R. China;Department of Computer Science, Zhejiang Normal University, Jinhua, P.R. China
Venue:
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
Year:
2012

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Abstract

With the increasing deployment of large-scale virtualized datacenters, using virtual machine (VM) migration technology to consolidate VMs is becoming very important for improving the efficiency of data center. The primary prerequisite for VM consolidation is to determine the best candidate VM for migration, and the most previous work targets only on optimizing single objective in VM selection. In this paper, we first propose a multi-objective optimization model based on detailed analysis of the impact of CPU temperature, resource usage and power consumption in VM selection. We then develop a VM selection algorithm to optimize the synthesized effect of VM migration, which will ultimately improve the system performance of physical machines (PMs). We further evaluate our algorithm by comprehensive experiments based on VM monitor Xen, and the results show that it can achieve the best tradeoffs among the resource usage, CPU temperature and power consumption of data center.