A Virtual Machine Scheduling Strategy with a Speed Switch and a Multi-Sleep Mode in Cloud Data Centers

  • Shunfu JinEmail author
  • Shanshan Hao
  • Xiuchen Qie
  • Wuyi Yue


With the rapid growth of energy costs and the constant promotion of environmental standards, energy consumption has become a significant expenditure for the operating and maintaining of a cloud data center. To improve the energy efficiency of cloud data centers, in this paper, we propose a Virtual Machine (VM) scheduling strategy with a speed switch and a multi-sleep mode. In accordance with the current traffic loads, a proportion of VMs operate at a low speed or a high speed, while the remaining VMs either sleep or operate at a high speed. Commensurate with our proposal, we develop a continuous-time queueing model with an adaptive service rate and a partial synchronous vacation. We construct a two dimensional Markov chain based on the total number of requests in the system and the state of all the VMs. Using a matrix geometric solution, we mathematically estimate the energy saving level and the response performance of the system. Numerical experiments with analysis and simulation show that our proposed VM scheduling strategy can effectively reduce the energy consumption without significant degradation in response performance. Additionally, we establish a system utility function to trade off the different performance measures. In order to determine the optimal sleep parameter and the maximum system utility function, we develop an improved Firefly intelligent searching Algorithm.


Cloud data center virtual machine scheduling speed switch multi-sleep matrix geometric solution utility function improved Firefly Algorithm 


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This work was supported in part by National Natural Science Foundation (Nos. 61872311, 61472342), Hebei Province Science Foundation of China (No. F2017203141), and was supported in part by MEXT, Japan. The authors would like to thank the anonymous referees for constructive comments which greatly improved the presentation of the paper.


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Copyright information

© Systems Engineering Society of China and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  • Shunfu Jin
    • 1
    Email author
  • Shanshan Hao
    • 1
  • Xiuchen Qie
    • 1
  • Wuyi Yue
    • 2
  1. 1.School of Information Science and EngineeringYanshan UniversityQinhuangdaoChina
  2. 2.Department of Intelligence and InformaticsKonan UniversityKobeJapan

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