Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (9): 2494-2503.doi: 10.23940/ijpe.19.09.p23.24942503

Previous Articles     Next Articles

Optimization of Multi-Objective Virtual Machine based on Ant Colony Intelligent Algorithm

Yuping Li*   

  1. School of Information Technology, Shangqiu Normal University, Shangqiu, 476000, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: *.E-mail address:

Abstract: In order to optimize the virtual machine consolidation process in data centers, improve the physical host utilization, and reduce the virtual machine migration cost, a novel multi-objective virtual machine consolidation algorithm using ant colony intelligence is designed in this paper. It optimizes two objectives that are ordered by their importance. The main objective of the proposed algorithm is to maximize the number of released physical hosts. Moreover, since virtual machine migration is a resource-intensive operation, it also seeks to minimize the amount of virtual machine migration. Our algorithm finally obtains the optimal virtual machine consolidation effect through a modified ant search process. Some contrast experiments are carried out with the other two kinds of typical ant algorithms. The experimental results show that, in all four test scenarios, under the condition of most scenarios and parameter configuration, our new algorithm achieves better performance on a number of released physical hosts in terms of the amount of virtual machine migration, the packing efficiency, and the algorithm running time.

Key words: virtual machine, multi-objective optimization, virtual machine migration, ant colony