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Scientific Programming
Volume 2018 (2018), Article ID 9471356, 10 pages
Research Article

Energy-Aware VM Initial Placement Strategy Based on BPSO in Cloud Computing

1School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2Beijing Institute of Control Engineering, Beijing 100190, China

Correspondence should be addressed to Xiong Fu

Received 22 September 2017; Revised 21 December 2017; Accepted 10 January 2018; Published 14 February 2018

Academic Editor: Emiliano Tramontana

Copyright © 2018 Xiong Fu et al. 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.


In recent years, high energy consumption has gradually become a prominent problem in a data center. With the advent of cloud computing, computing and storage resources are bringing greater challenges to energy consumption. Virtual machine (VM) initial placement plays an important role in affecting the size of energy consumption. In this paper, we use binary particle swarm optimization (BPSO) algorithm to design a VM placement strategy for low energy consumption measured by proposed energy efficiency fitness, and this strategy needs multiple iterations and updates for VM placement. Finally, the strategy proposed in this paper is compared with other four strategies through simulation experiments. The results show that our strategy for VM placement has better performance in reducing energy consumption than the other four strategies, and it can use less active hosts than others.