• DocumentCode
    2233518
  • Title

    The Research of Optimal Algorithm for Task Scheduling Underground Wireless Network Based on Distributed Computing

  • Author

    Ruan, Dian-xu ; Zhang, Xiao-guang ; Li, Hui ; Liu, Yin

  • Author_Institution
    Coll. of Mech. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    151
  • Lastpage
    155
  • Abstract
    To solve high real-time and complexity calculation problems such as feature extraction and pattern classification when wireless sensor network real-time diagnosis and equipment health record of the mine coal underground equipments monitoring, this paper purpose a optimal algorithm for task scheduling underground wireless monitoring network based on distributed computing, this method use the fast convergence feature of GA, combine the fish swarm algorithm with survival mechanism and GA, improves the global search capability and convergence rate, referring the advance of distributed computing model, introducing the distributed computing to wireless network task scheduling, with fish swarm genetic algorithm, it can balance resource loads. The simulation results show that this algorithm not only has very strong global search capability and convergence, but also improve the network lifetime.
  • Keywords
    computerised monitoring; convergence of numerical methods; distributed processing; genetic algorithms; resource allocation; scheduling; search problems; wireless sensor networks; GA; convergence rate; distributed computing; fish swarm genetic algorithm; global search; optimal algorithm; task scheduling; underground wireless monitoring network; wireless sensor network; WSN; distributed; mobile computing; monitoring; task scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Manufacturing Automation (ICMA), 2010 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-9018-9
  • Electronic_ISBN
    978-0-7695-4293-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2010.49
  • Filename
    5695171