• DocumentCode
    694729
  • Title

    An Energy-Saving Virtual-Machine Scheduling Algorithm of Cloud Computing System

  • Author

    Kehe Wu ; Ruo Du ; Long Chen ; Su Yan

  • Author_Institution
    Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
  • fYear
    2013
  • fDate
    7-8 Dec. 2013
  • Firstpage
    219
  • Lastpage
    224
  • Abstract
    Even virtual machines has been widely used as the unit to allocate the processor time or storage spaces by the providers of Cloud Computing systems, the energy consumption pattern of virtual machines in Cloud Computing system is not clear enough yet now. In this paper, we built an energy consumption model of the Cloud Computing system, by using statistical method we can estimate the energy consumption of a virtual machine in a small range of errors in 3%-6%. Then, based on the model, we proposed a virtual machine scheduling algorithm to improve the energy efficiency of the system. First, we set a threshold value of energy consumption for each server in the system, and by analyzing these work plans submitted by each virtual machine, we tested whether the threshold will been exceeded or not. Then, by migrate one/several chosen virtual machines to other physical servers in the system we can reduce the energy consumption of the whole system. Our evaluation shows that the proposed scheduling algorithm can effectively implement energy-saving goals without significant decline of the Quality of Services.
  • Keywords
    cloud computing; energy conservation; quality of service; scheduling; statistical analysis; virtual machines; cloud computing system; energy consumption estimation; energy consumption pattern; energy efficiency; energy-saving virtual machine scheduling algorithm; processor time; quality of services; scheduling algorithm; statistical method; storage space; Cloud computing; Computational modeling; Energy consumption; Scheduling algorithms; Servers; Virtual machining; cloud computing; energy consumption efficiency; energy consumption model; energy-saving; virtual machine scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
  • Conference_Location
    Guangzhou
  • Type

    conf

  • DOI
    10.1109/ISCC-C.2013.38
  • Filename
    6973595