IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i21p6030-d281753.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/21/6030/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/21/6030/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Assif Assad & Kusum Deep, 2018. "Harmony search based memetic algorithms for solving sudoku," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(4), pages 741-754, August.
    2. Mohammed Al-Betar & Ahamad Khader & Iyad Doush, 2014. "Memetic techniques for examination timetabling," Annals of Operations Research, Springer, vol. 218(1), pages 23-50, July.
    3. Abha Sharma & Pushpendra Kumar & Kanojia Sindhuben Babulal & Ahmed J. Obaid & Harshita Patel, 2022. "Categorical Data Clustering Using Harmony Search Algorithm for Healthcare Datasets," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 13(4), pages 1-15, August.
    4. R. A. Oude Vrielink & E. A. Jansen & E. W. Hans & J. Hillegersberg, 2019. "Practices in timetabling in higher education institutions: a systematic review," Annals of Operations Research, Springer, vol. 275(1), pages 145-160, April.
    5. Wei Sun & Yujun He & Hong Chang, 2015. "Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model," Energies, MDPI, vol. 8(2), pages 1-21, January.
    6. Raya-Armenta, Jose Maurilio & Bazmohammadi, Najmeh & Avina-Cervantes, Juan Gabriel & Sáez, Doris & Vasquez, Juan C. & Guerrero, Josep M., 2021. "Energy management system optimization in islanded microgrids: An overview and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    7. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    8. F. Paola & M. Giugni & F. Pugliese & P. Romano, 2018. "Optimal Design of LIDs in Urban Stormwater Systems Using a Harmony-Search Decision Support System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4933-4951, December.
    9. Lahasan, Badr Mohammed & Venkat, Ibrahim & Al-Betar, Mohammed Azmi & Lutfi, Syaheerah Lebai & Wilde, Philippe De, 2016. "Recognizing faces prone to occlusions and common variations using optimal face subgraphs," Applied Mathematics and Computation, Elsevier, vol. 283(C), pages 316-332.
    10. Hasan, Basima Hani F. & Abu Doush, Iyad & Al Maghayreh, Eslam & Alkhateeb, Faisal & Hamdan, Mohammad, 2014. "Hybridizing Harmony Search algorithm with different mutation operators for continuous problems," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 1166-1182.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:6030-:d:281753. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.