• DocumentCode
    189946
  • Title

    WSN sensor node placement approach based on Multi-objective Optimization

  • Author

    Abidin, H. Zainol ; Din, N.M. ; Radzi, N.A.M.

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2014
  • fDate
    14-16 April 2014
  • Firstpage
    111
  • Lastpage
    115
  • Abstract
    Wireless Sensor Network (WSN) with maximum coverage, minimum energy consumption and guaranteed connectivity can be achieved through an optimum sensor node placement scheme. A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. The MOTPSMA deployed in this paper uses the minimum uncovered area and minimum energy consumption as the objective functions subject to full connectivity constraint. The performance of the WSN deployed with MOTPSMA is then compared with another algorithm known as Multi-objective Evolutionary Algorithm based on Fuzzy Dominance (MOEA/DFD) in terms of coverage ratio, connectivity and energy consumption. Simulation results show that the WSN deployed with the proposed sensor node placement algorithm provides a larger coverage ratio, full connectivity and lower energy consumption.
  • Keywords
    optimisation; wireless sensor networks; DFD; MOEA; MOTPSMA; WSN; connectivity constraint; coverage ratio; energy consumption; fuzzy dominance; multiobjective evolutionary algorithm; multiobjective optimization; multiobjective territorial predator scent marking algorithm; objective functions; optimum sensor node placement scheme; wireless sensor network; Energy consumption; Evolutionary computation; Linear programming; Monitoring; Optimization; Region 10; Wireless sensor networks; Sensor node placement; WSN; biological inspired; connectivity; coverage; energy; multi-objective;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Region 10 Symposium, 2014 IEEE
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4799-2028-0
  • Type

    conf

  • DOI
    10.1109/TENCONSpring.2014.6863007
  • Filename
    6863007