• DocumentCode
    3250206
  • Title

    Robot assisted maintenance strategy in wireless sensor networks

  • Author

    Wu, Hao ; Cheng, Long ; Wu, Chengdong ; Chen, Li

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2012
  • fDate
    14-17 July 2012
  • Firstpage
    285
  • Lastpage
    288
  • Abstract
    In this paper, a robot assisted maintenance strategy (RAMS) which aims to balance the coverage rate and maintenance cost was proposed. In this strategy, we firstly analyzed the coverage and energy consumption model. And then a network health indicator which considering the coverage rate and residual energy in each node was proposed. Mathematically, the network health indicator is a cost function. So the network maintenance was formulated into cost optimization problem. Since the selection of candidate nodes which to be redeployed is very complexity, so the particle swarm optimal algorithm was employed to reduce the computation complexity. Finally, the robot was employed to repair the networks. Simulation results show that in comparison with random, uniform, and Delaney algorithm, the proposed RAMS can achieve relatively high coverage rate with much longer maintenance period.
  • Keywords
    mesh generation; particle swarm optimisation; robots; wireless sensor networks; Delaney algorithm; RAMS; computation complexity; cost optimization problem; coverage consumption model; energy consumption model; network health indicator; particle swarm optimal algorithm; robot assisted maintenance strategy; wireless sensor networks; Energy consumption; Maintenance engineering; Mobile communication; Random access memory; Robot sensing systems; Wireless sensor networks; Coverage Hole; Maintenance Cost; Network Maintenance; Wireless Sensor Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2012 7th International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-0241-8
  • Type

    conf

  • DOI
    10.1109/ICCSE.2012.6295075
  • Filename
    6295075