IDEAS home Printed from https://ideas.repec.org/a/igg/jdst00/v9y2018i1p39-54.html
   My bibliography  Save this article

Energy Efficient Resource Allocation During Initial Mapping of Virtual Machines to Servers in Cloud Datacenters

Author

Listed:
  • Nimisha Patel

    (Rai University, Ahmedabad, India & Sankalchand Patel College of Engineering, Visnagar, Gujarat, India)

  • Hiren Patel

    (LDRP Institute of Technology and Research, Gandhinagar, Gujarat, India)

Abstract

Energy consumption has been identified as one of the key research challenges during recent time in Cloud computing. Proper placement of Virtual Machines (VMs) on servers may address the issue. The process of placing VMs on servers can be divided into two phases viz. (a) Mapping of VMs on servers during the phase and (b) subsequent VM selection, migration and placement during consolidation phase. If the initial mapping is not efficient, subsequent operations may lead to unnecessary VM migrations, which in turn, may result into increase in migration cost and increase in SLA violations. In this research, the authors aim to improve the resource utilization to address these issues by keeping (i) the number of live server as minimal as possible for achieving energy efficiency, and (ii) the live server, as busy as possible by efficiently utilizing them. The authors conducted series of experiments with existing default technique and various other approaches. The results of our experiments make us conclude that there is a scope of improvement in the default mapping technique currently being used in CloudSim.

Suggested Citation

  • Nimisha Patel & Hiren Patel, 2018. "Energy Efficient Resource Allocation During Initial Mapping of Virtual Machines to Servers in Cloud Datacenters," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 9(1), pages 39-54, January.
    • Handle: RePEc:igg:jdst00:v:9:y:2018:i:1:p:39-54
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDST.2018010103
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jdst00:v:9:y:2018:i:1:p:39-54. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.