• DocumentCode
    1682667
  • Title

    Power management of distributed web savers by controlling server power state and traffic prediction for QoS

  • Author

    Imada, Takayuki ; Sato, Mitsuhisa ; Hotta, Yoshihiko ; Kimura, Hideaki

  • Author_Institution
    Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, we propose a scheme based on server node state control, including stand-by/wake-up and processor power control, to achieve aggressive power education while satisfying Quality of Service (QoS). Decreasing power consumption on Web servers is currently a challenging new problem to be solved in a data center or warehouse. Although Web servers are configured to have maximum performance, the actual access rate to the servers can be small in a specific period, such as midnight, so it may be possible to reduce the power consumption of the servers while satisfying QoS with lower server performance. In order to reduce power consumption on the server nodes, we now have to consider the power consumption of the entire node rather than only processor power by Dynamic Voltage and Frequency Scaling (DVFS). We implemented the proposed scheme to the distributed Web server system using the power-profile of server nodes and considering load increment based on traffic prediction method and evaluated the proposed scheme with a Web server benchmark workload based on SPECWeb99. The result reveals that the proposed scheme achieved an energy saving of approximately 17% with sufficient QoS performance on the distributed Web server system.
  • Keywords
    Internet; power consumption; power control; power engineering computing; DVFS; SPECWeb99; distributed Web servers system; dynamic voltage and frequency scaling; power consumption; power management; processor power control; quality of service; server power state control; traffic prediction method; Energy management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on
  • Conference_Location
    Miami, FL
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-1693-6
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2008.4536221
  • Filename
    4536221