• DocumentCode
    2670662
  • Title

    Power Control by Distribution Tree with Classified Power Capping in Cloud Computing

  • Author

    Wu, Zhengkai ; Wang, Jun

  • Author_Institution
    Comput. Sci., UCF, Orlando, FL, USA
  • fYear
    2010
  • fDate
    18-20 Dec. 2010
  • Firstpage
    319
  • Lastpage
    324
  • Abstract
    Power management is becoming very important in data centers. Cloud computing is also one of the newer promising techniques, that are appealing to many big companies. To apply power management in cloud computing has been proposed and considered as green computing. Cloud computing, due to its dynamic structure and property in online services, differs from current data centers in terms of power management. To better manage the power consumption of web services in cloud computing with dynamic user locations and behaviors, we propose a power budgeting design based on the logical level, using a distribution tree. By setting multiple trees, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs, e.g. response time) in terms of power characteristics. Base on these, we introduce classified power capping for different services as the control reference to maximize power saving when there are mixed workloads.
  • Keywords
    cloud computing; computer centres; environmental factors; power aware computing; classified power capping; cloud computing; data centers; distribution tree; green computing; power budgeting design; power control; power management; service level agreements; Classification tree analysis; Cloud computing; Computers; Energy consumption; Peer to peer computing; Power demand; Servers; Classified Power Capping; Cloud Comuting; Distribution Tree; Green Cloud; Power Budgeting; Power Consumption on the Logical Level; SLA;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom)
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-9779-9
  • Electronic_ISBN
    978-0-7695-4331-4
  • Type

    conf

  • DOI
    10.1109/GreenCom-CPSCom.2010.129
  • Filename
    5724846