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Perspective of virtual machine consolidation in cloud computing: a systematic survey

Author

Listed:
  • Junzhong Zou

    (Harbin University of Commerce)

  • Kai Wang

    (East University of Heilongjiang)

  • Keke Zhang

    (Khoury College of Computer Science)

  • Murizah Kassim

    (Universiti Teknologi MARA
    Universiti Teknologi MARA)

Abstract

Virtual Machine Consolidation (VMC) in cloud computing refers to the process of optimizing resource utilization by consolidating multiple Virtual Machines (VMs) onto fewer physical servers. This approach aims to maximize the efficiency of resource allocation, reduce operational costs, and enhance overall system performance. In general, effective VMC remains a cornerstone of efficient cloud infrastructure management, balancing resource efficiency with operational complexities to deliver reliable and cost-effective services. In this paper, we undertake a systematic survey of the essential steps in VMC within cloud computing environments. We focus on three critical phases: Physical Machines (PMs) detection, VMs selection, and VMs placement. The review comprehensively explores various aspects of VMC in cloud computing, including motivations, benefits, techniques, challenges, limitations, and applications. It also delves into the techniques and algorithms used for VMC, providing insights into state-of-the-art approaches. Meanwhile, the paper serves as a valuable resource for researchers interested in VMC, and provides a foundation for future research endeavors.

Suggested Citation

  • Junzhong Zou & Kai Wang & Keke Zhang & Murizah Kassim, 2024. "Perspective of virtual machine consolidation in cloud computing: a systematic survey," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 87(2), pages 257-285, October.
    • Handle: RePEc:spr:telsys:v:87:y:2024:i:2:d:10.1007_s11235-024-01184-9
    DOI: 10.1007/s11235-024-01184-9
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    References listed on IDEAS

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    1. Zhen Gao & Ning Zhao & Ning Xu & Ben Niu & Xudong Zhao, 2024. "Command filtering event-triggered secure control for nonlinear cyber-physical systems under denial-of-service attacks and input saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 55(9), pages 1851-1867, July.
    2. Chen Zheng & Yushu An & Zhanxi Wang & Xiansheng Qin & Benoît Eynard & Matthieu Bricogne & Julien Le Duigou & Yicha Zhang, 2023. "Knowledge-based engineering approach for defining robotic manufacturing system architectures," International Journal of Production Research, Taylor & Francis Journals, vol. 61(5), pages 1436-1454, March.
    3. Bhagyalakshmi Magotra & Deepti Malhotra, 2022. "Resource-Efficient VM Placement in the Cloud Environment Using Improved Particle Swarm Optimization," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-32, January.
    4. Min Shang & Ji Luo, 2021. "The Tapio Decoupling Principle and Key Strategies for Changing Factors of Chinese Urban Carbon Footprint Based on Cloud Computing," IJERPH, MDPI, vol. 18(4), pages 1-17, February.
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