• DocumentCode
    3336329
  • Title

    Grid resource scheduling algorithm based on QoS guided GA

  • Author

    Shi, Lei ; Xu, Hui-Hui

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Ji´´nan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    1281
  • Lastpage
    1285
  • Abstract
    Application of genetic algorithm (GA) for distribution and grid tasks scheduling has caused more and more academic concern. In this paper, the limitations of the existing genetic algorithm are analyzed. On the basis a grid resource scheduling algorithm based on QoS Guided GA is proposed, which takes these QoS factors into consideration including the priority of tasks, deadlines and budget constraints, etc; also, the encoding mechanism, fitness function, selection operator, crossover operator and mutation operator has been redesigned. Finally, the performance of the improved algorithm is simulated and compared with the original algorithm. The experimental results indicate that the improved algorithm can significantly reduce execution time consumption, and achieve high resource utilization.
  • Keywords
    genetic algorithms; grid computing; quality of service; resource allocation; QoS guided GA; crossover operator; distribution scheduling; encoding mechanism; execution time consumption reduction; fitness function; genetic algorithm; grid resource scheduling algorithm; grid task scheduling; mutation operator; resource utilization; selection operator; Bandwidth; Costs; Encoding; Genetic algorithms; Genetic engineering; Genetic mutations; Information science; Processor scheduling; Resource management; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-3928-7
  • Electronic_ISBN
    978-1-4244-3930-0
  • Type

    conf

  • DOI
    10.1109/ITIME.2009.5236264
  • Filename
    5236264