• DocumentCode
    2717710
  • Title

    A New Resource Management and Scheduling Model in Grid Computing Based on a Hybrid Genetic Algorithm

  • Author

    Tian, Hao

  • Author_Institution
    Dept. of Electron. Eng., Hubei Univ. of Econ., Hubei
  • Volume
    3
  • fYear
    2008
  • fDate
    3-4 Aug. 2008
  • Firstpage
    113
  • Lastpage
    117
  • Abstract
    Grid computing is one of the research hotspots in high performance computing area. Efficient scheduling of complex applications in a grid environment reveals several challenges due to its high heterogeneity, dynamic behavior, and space shared utilization. In this paper, we studied the characteristics of gird tasks, analyzed several main grid resource management models, and built a common model of grid tasks, put forward a hierarchy grid resource management and scheduling model, expounded the ideas of designing the model and described the details of it. Moreover, we proposed a hybrid genetic algorithm in its scheduling strategy, particularized the principle and the function of this algorithm as well as giving the concrete plan to put every step of the scheduling strategy into practice. Finally, the algorithm was simulated with the aid of SimGrid toolkit and it was proved an effective approach for grid scheduling.
  • Keywords
    genetic algorithms; grid computing; scheduling; gird tasks; grid computing; grid resource management; grid scheduling; high performance computing; hybrid genetic algorithm; resource scheduling; scheduling strategy; Computer networks; Distributed computing; Dynamic scheduling; Finishing; Genetic algorithms; Grid computing; High performance computing; Processor scheduling; Resource management; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3290-5
  • Type

    conf

  • DOI
    10.1109/CCCM.2008.285
  • Filename
    4609807