• DocumentCode
    1708039
  • Title

    A Joint Optimization Framework for Request Scheduling and Energy Storage Management in a Data Center

  • Author

    Shuang Chen ; Yanzhi Wang ; Pedram, Massoud

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2015
  • Firstpage
    163
  • Lastpage
    170
  • Abstract
    This paper addresses the problem of profit maximization for a data center with battery banks deployed at various levels of the power hierarchy. An optimization framework that covers the request dispatch, server resource allocation, and battery charging management is proposed. Instead of controlling the input/output power of the batteries after knowing the power profile of all other components of the data center as in a set of prior work, an optimal management policy is proposed which adjusts the power consumption (or supply) of servers and the battery banks at the same time. A response time dependent revenue model is adopted based on the delay estimation using the generalized processor sharing model. The rate capacity effect and the state of health degradation of the batteries, as well as the conversion and transmission loss in the power delivery network, are considered for the purpose of accurate power modeling and utility cost estimation. It is shown that the problem can be transformed into a series of convex optimization problems and then solved using standard solvers.
  • Keywords
    computer centres; convex programming; energy storage; resource allocation; battery banks; battery charging management; conversion; convex optimization problems; data center; delay estimation; energy storage management; generalized processor sharing model; optimal management policy; power delivery network; power hierarchy; power profile; rate capacity effect; request dispatch; request scheduling; response time dependent revenue model; server resource allocation; standard solvers; transmission loss; utility cost estimation; Arrays; Batteries; Degradation; Power demand; Servers; System-on-chip; Time factors; battery model; cloud computing; data center; state of health degradation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
  • Conference_Location
    New York City, NY
  • Print_ISBN
    978-1-4673-7286-2
  • Type

    conf

  • DOI
    10.1109/CLOUD.2015.31
  • Filename
    7214041