• DocumentCode
    2737031
  • Title

    Research on Grid Scheduling based on Modified Genetic Algorithm

  • Author

    Li, Wenzheng ; Yuan, Chi

  • Author_Institution
    Sch. of Comput., Beijing Technol. & Bus. Univ., Beijing
  • Volume
    2
  • fYear
    2008
  • fDate
    6-8 Oct. 2008
  • Firstpage
    633
  • Lastpage
    638
  • Abstract
    The dissertation consists of six chapters. In the first chapter, we present basic notions and relevant results in the area of grid scheduling. We understand that the current approaches of GA have little weaknesses when it was used in grid scheduling. This inspires us to study the method of MGA (modified genetic algorithm) to solve grid-scheduling problems. Consequently, in the second and the third chapter, we introduce mathematical model of grid scheduling and give a detailed MGA method by using the "pattern theory" and "building block hypothesis" technologies. This modified method can decrease the randomicity of the current GA. In the fourth chapter, we use the MGA method to study grid-scheduling problems and find a necessary and sufficient design method. In the latter chapters, we analyze the laboratory result to show that the modified algorithm has better characteristics than the standard GA when it was used in task scheduling.
  • Keywords
    genetic algorithms; grid computing; scheduling; building block hypothesis; grid scheduling; modified genetic algorithm; pattern theory; task scheduling; Algorithm design and analysis; Design methodology; Genetic algorithms; Grid computing; Laboratories; Mathematical model; NP-complete problem; Processor scheduling; Resource management; Scheduling algorithm; Genetic Algorithm; Grid; Pattern Theory; Task Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
  • Conference_Location
    Alexandria
  • Print_ISBN
    978-1-4244-2020-9
  • Electronic_ISBN
    978-1-4244-2021-6
  • Type

    conf

  • DOI
    10.1109/ICPCA.2008.4783688
  • Filename
    4783688