• DocumentCode
    1603753
  • Title

    A Model Predictive Approach to Fault-Tolerant WASNs

  • Author

    Papalini, Michele ; Polzonetti, Alberto ; Riganelli, Oliviero

  • Author_Institution
    Dipt. di Mat. e Inf., Univ. di Camerino, Camerino
  • fYear
    2009
  • Firstpage
    348
  • Lastpage
    353
  • Abstract
    In wireless ad hoc sensor networks (WASNs), a crucial issue is to reduce power consumption while satisfying some key network properties. In this paper, we propose a fault-tolerant topology control that optimizes the lifetime of the network at a given degree k of connectivity by minimizing power consumption. Our topology control is fully distributed and uses a model-based transmission power adaptation strategy based on model-predictive control. Specifically, the future network behavior is predicted in order to derive an optimal transmission power assignment which tracks the desired connectivity level minimizing energy. Our experimental results show that our localized solution is more scalable and requires much less communication bandwidth and energy than the centralized approach.
  • Keywords
    ad hoc networks; distributed control; fault tolerance; predictive control; telecommunication control; telecommunication network reliability; telecommunication network topology; wireless sensor networks; distributed control; fault tolerant WASN; model based transmission power adaptation strategy; network lifetime; power consumption reduction; predictive approach; topology control; wireless ad hoc sensor network; Batteries; Distributed control; Energy consumption; Fault tolerance; Network topology; Predictive models; Robustness; Sensor systems; Wireless communication; Wireless sensor networks; WASN; fault-tolerant; model predictive; wireless ad hoc sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking and Services, 2009. ICNS '09. Fifth International Conference on
  • Conference_Location
    Valencia
  • Print_ISBN
    978-1-4244-3688-0
  • Electronic_ISBN
    978-0-7695-3586-9
  • Type

    conf

  • DOI
    10.1109/ICNS.2009.84
  • Filename
    4976784