• DocumentCode
    3242148
  • Title

    An efficient optimization technique for task matching and scheduling in heterogeneous computing systems

  • Author

    Chuang, Po-Jen ; Wei, Chia-Hsin

  • Author_Institution
    Dept. of Electr. Eng., Tamkang Univ., Taipei Hsien, Taiwan
  • fYear
    2002
  • fDate
    17-20 Dec. 2002
  • Firstpage
    419
  • Lastpage
    424
  • Abstract
    A new optimization technique, the genetic annealing algorithm (GAA), is proposed to solve the task matching and scheduling problem in a heterogeneous computing system. The GAA is simple in design; it employs only the stir operation, a novel idea with the annealing concept, to locate optimal solutions. Experimental evaluation shows that compared with the genetic algorithm, simulated annealing and guided evolutionary simulated annealing approaches, the GAA yields constantly favorable performance in terms of speedup, running time, cost and complexity.
  • Keywords
    distributed processing; genetic algorithms; processor scheduling; simulated annealing; genetic algorithm; genetic annealing algorithm; guided evolutionary simulated annealing; heterogeneous computing system; optimization; task matching; task scheduling; Concurrent computing; Distributed computing; Processor scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Systems, 2002. Proceedings. Ninth International Conference on
  • ISSN
    1521-9097
  • Print_ISBN
    0-7695-1760-9
  • Type

    conf

  • DOI
    10.1109/ICPADS.2002.1183433
  • Filename
    1183433