• DocumentCode
    3587525
  • Title

    Congestion detection in Wireless sensor network using neural network

  • Author

    Singhal, Prakul ; Yadav, Anamika

  • Author_Institution
    Dept. of Electr. Eng., Nat. Inst. of Technol., Raipur, Raipur, India
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In Wireless sensor network (WSN), sink nodes are bottleneck of network due to congestion. Congestion deteriorates the overall performance of the system. So congestion detection in a WSN is very vital issue in the present scenario. In this paper, artificial neural network based congestion detection algorithm is developed. The neural network based congestion detection system uses number of participants, buffer occupancy, and traffic rate as input parameters and gives the congestion level as output. A number of NS-2 and MATLAB simulation results show that the proposed scheme accurately detects the congestion level and represents the state of congestion in the WSN.
  • Keywords
    Internet; neural nets; telecommunication congestion control; wireless sensor networks; Matlab simulation; NS-2; WSN; artificial neural network based congestion detection algorithm; buffer occupancy; congestion level; input parameters; participant number; sink nodes; traffic rate; wireless sensor network; Artificial neural networks; Biological neural networks; MATLAB; Protocols; Training; Wireless sensor networks; Buffer occupancy; Congestion detection; Neural network; Traffic rate; Wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Convergence of Technology (I2CT), 2014 International Conference for
  • Print_ISBN
    978-1-4799-3758-5
  • Type

    conf

  • DOI
    10.1109/I2CT.2014.7092259
  • Filename
    7092259