• DocumentCode
    3309236
  • Title

    On maximum lifetime routing in Wireless Sensor Networks

  • Author

    Ning, Xu ; Cassandras, Christos G.

  • Author_Institution
    Microsoft Corp., Redmond, WA, USA
  • fYear
    2009
  • fDate
    15-18 Dec. 2009
  • Firstpage
    3757
  • Lastpage
    3762
  • Abstract
    Lifetime maximization is an important optimization problem specific to wireless sensor networks (WSNs) since they operate with limited energy resources which are therefore eventually depleted. This paper considers first the problem of routing in a WSN with the objective of lifetime maximization based on a simple model for battery dynamics. Specifically, we discuss the equivalence of two different formulations and solutions in the existing literature. We then revisit a related problem, the optimal allocation of a total energy amount over all nodes so as to maximize network lifetime. We prove that this is equivalent to a shortest path problem on a weighted graph and can therefore be efficiently solved. Finally, we present a more realistic model for battery dynamics, and numerically solve the lifetime maximization problem. The empirical results obtained indicate that, while a static routing policy is not expected to be optimal, such a policy is a good approximation of the optimal dynamic routing policy.
  • Keywords
    energy resources; optimisation; telecommunication network routing; wireless sensor networks; battery dynamics; lifetime maximization; limited energy resources; maximum lifetime routing; optimal allocation; optimal dynamic routing policy; shortest path problem; wireless sensor networks; Base stations; Batteries; Costs; Energy consumption; Optimal control; Routing; Shortest path problem; Systems engineering and theory; USA Councils; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
  • Conference_Location
    Shanghai
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-3871-6
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2009.5400394
  • Filename
    5400394