• DocumentCode
    1957160
  • Title

    Just-in-Time Server Provisioning Using Virtual Machine Standby and Request Prediction

  • Author

    Machida, Fumio ; Kawato, Masahiro ; Maeno, Yoshiharu

  • Author_Institution
    Service Platforms Res. Labs., NEC Corp., Kawasaki
  • fYear
    2008
  • fDate
    2-6 June 2008
  • Firstpage
    163
  • Lastpage
    171
  • Abstract
    Server provisioning is a practical technique to reconfigure a shared server and to improve resource utilization of servers in datacenters and enterprise systems. For the complex systems, however, long process of server provisioning impedes prompt solutions to system problems. This paper proposes a technique to shorten the provisioning processing time after the occurrence of the provisioning request by speculative provisioning execution on a virtual machine as standby. In order to start the provisioning execution in advance, a prediction method for the provisioning request is required. This paper presents a prediction model based on the logistic regression model using system performance metrics. From the evaluation using the actual performance data of enterprise systems, for 50% of the server provisioning requests, the provisioning processing time after the request is shorten over 10 minutes by using the 20-minutes look-ahead request prediction model.
  • Keywords
    regression analysis; resource allocation; virtual machines; just-in-time server; logistic regression model; prediction model; server provisioning; system performance metrics; virtual machine standby system; Automation; Control systems; Laboratories; Logistics; National electric code; Network servers; Predictive models; Resource management; Storage area networks; Virtual machining; Provisioning; logistic regression; standby; virtual machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomic Computing, 2008. ICAC '08. International Conference on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-0-7695-3175-5
  • Electronic_ISBN
    978-0-7695-3175-5
  • Type

    conf

  • DOI
    10.1109/ICAC.2008.13
  • Filename
    4550837