• DocumentCode
    997581
  • Title

    Solutions for the “Silent Node” Problem in an Automatic Meter Reading System Using Power-Line Communications

  • Author

    Gao, Q. ; Yu, J.Y. ; Chong, P.H.J. ; So, P.L. ; Gunawan, E.

  • Author_Institution
    Nanyang Technol. Univ., Singapore
  • Volume
    23
  • Issue
    1
  • fYear
    2008
  • Firstpage
    150
  • Lastpage
    156
  • Abstract
    This paper presents two algorithms, namely clustered simple polling and neighbor relay polling, for solving the typical "silent node" problem in automatic meter reading (AMR) systems using power-line communications (PLC)-access networks. These schemes are tested through computer simulations to be both effective and efficient in overcoming the "silent node" problem in AMR systems. The construction of the PLC-access network model in this paper is based on the actual structure of the PLC-access networks of Singapore public residential buildings. Also, a two-state transition Markov model is used to simulate a meter unit with such a "silent node" problem in a PLC network. The processing time model is established on a meter topology of three-level clustering. By using these models for our computer simulations, the performance of our proposed schemes can be evaluated in terms of reliability and efficiency.
  • Keywords
    Markov processes; automatic meter reading; carrier transmission on power lines; PLC-access network; automatic meter reading system; clustered simple polling; meter topology; neighbor relay polling; power-line communications; processing time model; silent node problem; three-level clustering; two-state transition Markov model; Automatic meter reading; Buildings; Clustering algorithms; Computational modeling; Computer simulation; Network topology; Power system modeling; Power system relaying; Programmable control; System testing; Automatic meter reading (AMR); polling; power-line communications (PLC);
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2007.910990
  • Filename
    4395167