• DocumentCode
    1642293
  • Title

    A Subproblem-dependent Heuristic in MOEA/D for the Deployment and Power Assignment Problem in Wireless Sensor Networks

  • Author

    Konstantinidis, Andreas ; Zhang, Qingfu ; Yang, Kun

  • Author_Institution
    Sch. of Comput. Sci. & Electron. Eng., Univ. of Essex, Colchester
  • fYear
    2009
  • Firstpage
    2740
  • Lastpage
    2747
  • Abstract
    In this paper, we propose a Subproblem-dependent Heuristic (SH) for MOEA/D to deal with the Deployment and Power Assignment Problem (DPAP) in Wireless Sensor Networks (WSNs). The goal of the DPAP is to assign locations and transmit power levels to sensor nodes for maximizing the network coverage and lifetime objectives. In our method, the DPAP is decomposed into a number of scalar subproblems. The subproblems are optimized in parallel, by using neighborhood information and problem-specific knowledge. The proposed SH probabilistically alternates between two DPAP-specific strategies based on the subproblems objective preferences. Simulation results have shown that MOEA/D performs better than NSGA-II in several WSN instances.
  • Keywords
    genetic algorithms; wireless sensor networks; lifetime objectives; neighborhood information; network coverage; power assignment problem; problem-specific knowledge; subproblem-dependent heuristic; wireless sensor networks; Computer science; Constraint optimization; Evolutionary computation; Genetics; Monitoring; Network topology; Power engineering and energy; Sensor systems; Sorting; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983286
  • Filename
    4983286