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An Efficient Representation Using Harmony Search for Solving the Virtual Machine Consolidation

Author

Listed:
  • MinJun Kim

    (Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea)

  • JuneSeok Hong

    (Department of Management Information Systems, Kyonggi University, 155-42, Gwanggyosan-ro, Suwon 16227, Korea)

  • Wooju Kim

    (Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea)

Abstract

A data center with a large number of servers, large storage, and many network devices requires power for cooling to reduce heat generation, air conditioning, and emergency power generation facilities, in addition to power for operation internally consumed by infrastructure equipment. The power consumed by data centers worldwide makes up a large proportion. Although the size of data centers is expected to increase, we are already faced with power problems because stability is prioritized over efficiency when operating data centers in order to meet the Service Level Agreement (SLA) conditions. Most data centers are in a virtualization environment, and virtual machine consolidation using physical machine (PM) transitions to the idle mode through virtual machine (VM) migration has been suggested as one of the most effective ways to reduce the amount of power usage in a data center. This study takes into account the characteristics of virtualization environments and presents an algorithm that effectively solves VM consolidation (VMC) through operator design using a grouping representation method and a meta-heuristic method known as harmony search.

Suggested Citation

  • MinJun Kim & JuneSeok Hong & Wooju Kim, 2019. "An Efficient Representation Using Harmony Search for Solving the Virtual Machine Consolidation," Sustainability, MDPI, vol. 11(21), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:6030-:d:281753
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    References listed on IDEAS

    as
    1. Ho-Yoeng Yun & Suk-Jae Jeong & Kyung-Sup Kim, 2013. "Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-8, November.
    2. Mohammed Al-Betar & Ahamad Khader, 2012. "A harmony search algorithm for university course timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 3-31, April.
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