Optimal virtual machine placement with multiple resources constraints in cloud data centers

Issue title: Special Section: Intelligent Algorithms for Complex Information Services - Recent Advances and Future Trends

Guest editors: Andino Maseleno, Xiaohui Yuan and Valentina E. Balas

Article type: Research Article

Authors: He, Zhenxiang^*; | Li, Zhenjiang | Zhang, Shengcai | Lu, Jun

Affiliations: School of Cyberspace Security, Gansu University of Politics Science and Law, LanZhou, China

Correspondence: [*] Corresponding author. Zhenxiang He, School of Cyberspace Security, Gansu University of Politics Science and Law, LanZhou, China. E-mail: [email protected].

Abstract: In cloud data centers, different virtual machine placement strategies will affect the resource utilization efficiency of the whole system. How to improve the overall resource utilization of the system by adjusting the virtual machine placement strategy under limited resources is the focus of current researchers. In this paper, a new virtual machine placement strategy is proposed, which is based on the comprehensive constraints of various system resources. In the process of solving the problem, a multi-objective ant colony optimization algorithm is used. Simulation results show that this method can effectively reduce the number of physical machines activated in the data center, and the accuracy is high.

Keywords: Cloud data center, virtual machine placement, multiple resources constraints, ant colony optimization

DOI: 10.3233/JIFS-189001

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5161-5170, 2020