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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 816518, 8 pages
Research Article

Energy Efficient Multiresource Allocation of Virtual Machine Based on PSO in Cloud Data Center

1Department of Computer Science and Engineering, University of Electronic Science and Technology, Chengdu 610054, China
2Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received 3 March 2014; Accepted 26 May 2014; Published 12 June 2014

Academic Editor: Qinggang Meng

Copyright © 2014 An-ping Xiong and Chun-xiang Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Presently, massive energy consumption in cloud data center tends to be an escalating threat to the environment. To reduce energy consumption in cloud data center, an energy efficient virtual machine allocation algorithm is proposed in this paper based on a proposed energy efficient multiresource allocation model and the particle swarm optimization (PSO) method. In this algorithm, the fitness function of PSO is defined as the total Euclidean distance to determine the optimal point between resource utilization and energy consumption. This algorithm can avoid falling into local optima which is common in traditional heuristic algorithms. Compared to traditional heuristic algorithms MBFD and MBFH, our algorithm shows significantly energy savings in cloud data center and also makes the utilization of system resources reasonable at the same time.