J4 ›› 2015, Vol. 42 ›› Issue (3): 173-178+185.doi: 10.3969/j.issn.1001-2400.2015.03.029

• Original Articles • Previous Articles     Next Articles

Multi-objective ant colony optimization algorithm for  virtual machine placement

ZHAO Jun;MA Zhong;LIU Chi;LI Haishan;WANG Xinyu   

  1. (Wuhan Digital Engineering Institute, Wuhan  430074, China)
  • Received:2014-02-13 Online:2015-06-20 Published:2015-07-27
  • Contact: ZHAO Jun E-mail:57278201@qq.com

Abstract:

The virtual machine placement schemes for existing data centers are mostly concentrated on optimization of energy consumption and resource waste. However, the optimization of datacenter network traffic was rarely considered, which may affect the network scalability. Therefore, with the consideration of both resource waste and total network traffic, this paper models the virtual machine placement as a multi-objective optimization problem, which optimizes the following two objectives in one time for data centers, i.e., minimizing physical machine resources to improve the physical machine efficiency and minimizing total network traffic to improve the network scalability. To solve this problem, we have designed a virtual machine placement algorithm based on multi-objective ant colony optimization (MOACO). Experimental results show that the proposed algorithm can effectively reduce physical machine resources waste and total network traffic compared with the FFD algorithm.

Key words: virtual machine placement, multi-objective ant colony optimization, total network traffic

CLC Number: 

  • TP301