• DocumentCode
    3768441
  • Title

    Scheduling strategy based on genetic algorithm for Cloud computer energy optimization

  • Author

    Huang Zhen Jin; Lu Yang; Ouyang Hao

  • Author_Institution
    School of computer and information, Hefei University of Technology, China
  • fYear
    2015
  • Firstpage
    516
  • Lastpage
    519
  • Abstract
    During the processing of Cloud platform it will generate a large amount of energy consumption. so how to improve energy efficiency become increasingly important. This paper presents a scheduling strategy which is based on the genetic algorithm for Cloud computing energy optimal. First, we adopt queuing network for system modeling and prove that the energy consumption of Cloud computing system is determined by the task scheduling probability. In order to obtain minimum energy consumption, genetic algorithms based on optimal reservation selection is use to optimize the dispatch probability. Simulation results show that this method is feasible to optimize energy consumption of cloud computing system.
  • Keywords
    "Energy efficiency","Cloud computing","Indium phosphide","III-V semiconductor materials","Sociology","Statistics","Analytical models"
  • Publisher
    ieee
  • Conference_Titel
    Communication Problem-Solving (ICCP), 2015 IEEE International Conference on
  • Print_ISBN
    978-1-4673-6543-7
  • Type

    conf

  • DOI
    10.1109/ICCPS.2015.7454218
  • Filename
    7454218