• DocumentCode
    686347
  • Title

    An activity-based replica placement method of energy-conservation

  • Author

    Xiao-Yong Zhao ; Lei Wang

  • Author_Institution
    Sch. of Inf. Manage., Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • fYear
    2013
  • fDate
    6-8 Dec. 2013
  • Firstpage
    446
  • Lastpage
    451
  • Abstract
    Aiming at the problems of increasing energy consumption of cloud storage, big environmental resources pressure, exist research on replica placement lacking of focus on energy consumption, this paper proposes a energy conservation replica placement method ECRP(Energy Conservation Replica Placement, ECRP). Based on the three main different levels of energy consumption of hardware components, the data node is divided into hot zone, warm zone and cold zone three logical zone, each zone uses different power management strategies and replica placement strategies, and after building a file activity prediction model which based on the simulated annealing BP neural network, files are stored in the data nodes on different zone according to the type of file activity, and then calculate the file activity periodically, when file activity exceeds a certain threshold, the file begins flow among the hot zone, warm zone and cold zone step by step in the two-way. Experiment results show that this method better solve the problems of replica placement and energy consumption optimization, have good energy saving effect.
  • Keywords
    backpropagation; energy conservation; energy consumption; neural nets; simulated annealing; ECRP; activity-based replica placement method; cloud storage; cold zone; data node; energy conservation replica placement method; energy consumption optimization; energy saving effect; environmental resources pressure; file activity prediction model; hardware components; hot zone; logical zone; management strategies; replica placement strategies; simulated annealing BP neural network; warm zone; Cloud computing; Data models; Educational institutions; Energy consumption; Neural networks; Predictive models; Simulated annealing; energy conserving; file activity; neural network; replica placement; simulated anneal;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Theory and Its Applications (iFUZZY), 2013 International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/iFuzzy.2013.6825481
  • Filename
    6825481