• DocumentCode
    3567261
  • Title

    Dynamic power management in a wireless sensor network using predictive control

  • Author

    Mokrenko, Olesia ; Lesecq, Suzanne ; Lombardi, Warody ; Puschini, Diego ; Albea, Carolina ; Debicki, Olivier

  • Author_Institution
    Univ. Grenoble Alpes, Grenoble, France
  • fYear
    2014
  • Firstpage
    4756
  • Lastpage
    4761
  • Abstract
    Technological advances have made wireless sensor nodes cheap and reliable enough to be brought into various application domains. These nodes are powered by battery, thus they have a limited lifespan which is a major drawback for their acceptance. This paper addresses a power consumption control problem of wireless nodes equipped with batteries. Dynamic power management is used to dynamically re-configure the set of sensor nodes in order to provide given services and performance levels with a minimum number of active nodes and/or a minimum load on such components. The power control formulation is based on model predictive control with constraints and binary optimization variables, leading to a mixed integer quadratic programming problem. Simulations are performed to demonstrate the efficiency of the proposed control method.
  • Keywords
    integer programming; optimisation; power consumption; power control; predictive control; quadratic programming; telecommunication network reliability; wireless sensor networks; active nodes; battery power; binary optimization variables; dynamic power management; limited lifespan; minimum load; mixed integer quadratic programming problem; power consumption control problem; power control formulation; predictive control; sensor node reconfiguration reliability; technological advances; wireless sensor network; Batteries; Power control; Power demand; Silicon; Tin; Wireless communication; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2014 - 40th Annual Conference of the IEEE
  • Type

    conf

  • DOI
    10.1109/IECON.2014.7049220
  • Filename
    7049220