VMs Placement Strategy based on Distributed Parallel Ant Colony Optimization Algorithm

Authors

Gaochao Xu, College of Computer Science and Technology, Jilin University, Changchun, China\\ Symbol Computation and Knowledge Engineer of Ministry of Education, JiLin University, Changchun, ChinaFollow
Yushuang Dong, College of Computer Science and Technology, Jilin University, Changchun, China\\ Symbol Computation and Knowledge Engineer of Ministry of Education, JiLin University, Changchun, ChinaFollow
Xiaodong Fu, College of Computer Science and Technology, Jilin University, Changchun, China\\ Symbol Computation and Knowledge Engineer of Ministry of Education, JiLin University, Changchun, ChinaFollow

Author Country (or Countries)

China

Abstract

Cloud computing is at the forefront of information technology. Cloud computing led to abandon the use of expensive mainframe. It becomes a trend that data center uses the cluster which is relatively cheap and virtualization technologies to provide infrastructure services. To improve the utilization rate of the cloud center and decrease the operating cost, the cloud center provides services to users as required by sharding the resources with virtualization. Because consideration should be given to both QoS for users and cost saving for cloud computing providers, cloud providers try to maximize performance and minimize energy cost as well. In this paper, we propose a Distributed Parallel Ant Colony Optimization (DPACO) Algorithm of placement strategy for live virtual machines Live Migration on cloud platform. It executes the ant colony optimization algorithm parallelly and distributedly on several selected physical hosts in the first stage. Then it continues to execute the second stage ant colony optimization algorithm with solutions calculated by the first stage. The solution calculated by the second stage ant colony optimization algorithm is the optimal solution of our approach. The experimental results have shown that the proposed placement strategy of VM live migration is more effective and energy-efficient with ensuring QoS for users than other placement strategies on the cloud platform.

Recommended Citation

Xu, Gaochao; Dong, Yushuang; and Fu, Xiaodong (2015) "VMs Placement Strategy based on Distributed Parallel Ant Colony Optimization Algorithm," Applied Mathematics & Information Sciences: Vol. 09: Iss. 2, Article 36.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol09/iss2/36