• DocumentCode
    1148522
  • Title

    Energy-Efficient Routing for Signal Detection in Wireless Sensor Networks

  • Author

    Yang, Yang ; Blum, Rick S. ; Sadler, Brian M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Lehigh Univ., Bethlehem, PA
  • Volume
    57
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    2050
  • Lastpage
    2063
  • Abstract
    For many envisioned applications of wireless sensor networks (WSNs), the information processing involves dealing with distributed data in the context of accurate signal detection and energy-efficient routing, which have been active research topics for many years, respectively. In this paper, we relate these two aspects via joint optimization. Considering the scenario of using distributed radar-like sensors to detect the presence of an object through active sensing, we formulate the problem of energy- efficient routing for signal detection under the Neyman-Pearson criterion, apparently for the first time. The joint optimization of detection and routing is carried out in a fusion center which precomputes the routes as a function of the geographic location to be monitored. Accordingly, we propose three different routing metrics that aim at an appropriate tradeoff between the detection performance and the energy expenditure. In particular, each metric relates the detection performance explicitly in terms of probabilities of detection and false alarm, with the energy consumed in sensing and routing. The routing problems are formulated as combinatorial optimization programs, and we provide solutions drawing on operations research. We present extensive simulation results that demonstrate the energy and detection performance tradeoffs for each proposed routing metric.
  • Keywords
    signal detection; telecommunication network routing; wireless sensor networks; Lagrangian relaxation; combinatorial optimization; constrained shortest path; energy efficiency; energy-efficient routing; parametric shortest path; signal detection; wireless sensor networks; Combinatorial optimization; Lagrangian relaxation; Neyman–Pearson criterion; constrained shortest path; energy efficiency; parametric shortest path; routing; signal detection; wireless sensor networks;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2009.2014814
  • Filename
    4776475