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Simultaneous application assignment and virtual machine placement via ant colony optimization for energy-efficient enterprise data centers

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Abstract

Enterprise cloud data centers consume a tremendous amount of energy due to the large number of physical machines (PMs). These PMs host a huge number of virtual machines (VMs), on which a vast number of applications are deployed. Existing research uses two separate layers to manage data center resources: application assignment to VMs, and VM placement to PMs, each of which is a bin packing problem. While this consecutive two-layer bin packing (Consec2LBP) makes the problems easier to solve, it also limits further improvement in the quality of solution. To address this issue, an integrated any colony optimization approach is proposed in this paper to deal with both layers simultaneously. It formulates the two-layer resource management into an integrated two-layer bin packing (Int2LBP) optimization problem. Then, an integrated first fit-decreasing (FFD) algorithm Int2LBP_FFD is proposed to solve this optimization problem. Using the result of Int2LBP_FFD as an initial solution, an integrated ant colony system (ACS) algorithm Int2LBP_ACS is further developed to improve the quality of solution. Simulation experiments are conducted to demonstrate the effectiveness of our integrated approach.

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Acknowledgements

This work was supported in part by the Australian Research Council through the Discovery Project Scheme under Grant DP170103305. Author F. Alharbi would like to acknowledge Shaqra University of Saudi Arabia for its financial support through the Saudi Arabian Culture Mission in Australia under Scholarship Ref No. 11954813

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Author notes

  1. Fares Alharbi

    Present address: Shaqra University, Shaqra, Riyadh, 11961, Saudi Arabia

Authors and Affiliations

  1. School of Computer Science, Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia

    Fares Alharbi, Yu-Chu Tian & Maolin Tang

  2. Melbourne Institute of Technology, Melbourne, VIC, 3000, Australia

    Md Hasanul Ferdaus

  3. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Wei-Zhe Zhang

  4. The Key Laboratory of Intelligent Computing and Information Processing of the Ministry of Education of China, Xiangtan University, Xiangtan, 411105, Hunan, China

    Zu-Guo Yu

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  1. Fares Alharbi
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Correspondence to Yu-Chu Tian.

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Alharbi, F., Tian, YC., Tang, M. et al. Simultaneous application assignment and virtual machine placement via ant colony optimization for energy-efficient enterprise data centers. Cluster Comput 24, 1255–1275 (2021). https://doi.org/10.1007/s10586-020-03186-z

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  • DOI: https://doi.org/10.1007/s10586-020-03186-z

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