• DocumentCode
    2664222
  • Title

    LGR: The New Genetic Based Scheduler for Grid Computing Systems

  • Author

    Khanli, Leili Mohammad ; Razavi, Seyed Naser

  • Author_Institution
    Tabriz Univ., Tabriz, Iran
  • fYear
    2008
  • fDate
    10-12 Dec. 2008
  • Firstpage
    639
  • Lastpage
    644
  • Abstract
    The computational grid provides a promising platform for the deployment of various high-performance computing applications. In computational grid, an efficient scheduling of task onto the processors that minimizes the entire execution time is vital for achieving a high performance. Solving this problem is very hard and many attempts have been made to solve the problem. Using classical algorithms, With regard to the complexity of this problem, is not the good way; so the indefinite method acts better than classical method. Evolutionary algorithms are the best choice for solving this hard problem. In this paper, contrary to prior ways, the new string representation has been used, communication costs has not been ignored and presents as a major factor for reaching to optimum solution.
  • Keywords
    genetic algorithms; grid computing; processor scheduling; classical method; computational grid; evolutionary algorithms; genetic based scheduler; grid computing systems; high-performance computing; indefinite method; string representation; Computer applications; Computer networks; Costs; Genetic algorithms; Grid computing; High performance computing; Optimal scheduling; Power engineering computing; Processor scheduling; Scheduling algorithm; Genetic Algorithm; Grid Computing Systems; LGR; Scheduler;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling Control & Automation, 2008 International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    978-0-7695-3514-2
  • Type

    conf

  • DOI
    10.1109/CIMCA.2008.30
  • Filename
    5172700