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Energy-efficient migration and consolidation algorithm of virtual machines in data centers for cloud computing

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Abstract

In this paper, we developed a dynamic energy-efficient virtual machine (VM) migration and consolidation algorithm based on a multi-resource energy-efficient model. It can minimize energy consumption with Quality of Service guarantee. In our algorithm, we designed a method of double threshold with multi-resource utilization to trigger the migration of VMs. The Modified Particle Swarm Optimization method is introduced into the consolidation of VMs to avoid falling into local optima which is a common defect in traditional heuristic algorithms. Comparing with the popular traditional heuristic algorithm Modified Best Fit Decrease, our algorithm reduced the number of active physical nodes and the amount of VMs migrations. It shows better energy efficiency in data center for cloud computing.

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Acknowledgments

This paper was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No. KJ130514), Research Program of Chongqing Science and Technology Commission (Grant No. cstc2015jcyjA0420) and Natural Science Foundation of Chongqing University of Posts and Telecommunications (Grant No. A2012-31). We also thanks Linpeng He and Chao Dong from Nicholls State University and Chen He from University of Nebraska-Lincoln for suggestion on this study.

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Correspondence to Hongjian Li.

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Li, H., Zhu, G., Cui, C. et al. Energy-efficient migration and consolidation algorithm of virtual machines in data centers for cloud computing. Computing 98, 303–317 (2016). https://doi.org/10.1007/s00607-015-0467-4

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