• DocumentCode
    2872916
  • Title

    An approach for maximum lifetime data gathering with aggregation issue in wireless sensor networks

  • Author

    Kong, Ruirui

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Qingdao Univ. of Sci. & Technol., Qingdao, China
  • Volume
    11
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    Saving energy and prolonging network lifetime are key issues of wireless sensor networks. In this paper we consider the problem of Maximum Lifetime data gathering in wireless sensor networks. This is a NP-hard problem and the size of the solution, which consists of a collection of aggregation trees together with the number of rounds each such tree should be used, is desired to be small, given the limited computation and communication resources of sensor nodes. We describe a simple and efficient combinatorial iterative algorithm for finding an optimal continuous solution that has up to n-1 aggregation trees and achieves lifetime, which depends on the network topology and initial energy available at the sensors. We obtain an approximate optimal integral solution by simply optimal continuous solution. The simulation experiment is shown that the RSM algorithm for computing maximum lifetime is more effective.
  • Keywords
    combinatorial mathematics; computational complexity; iterative methods; sensor fusion; trees (mathematics); wireless sensor networks; NP hard problem; RSM algorithm; aggregation issue; aggregation tree; combinatorial iterative algorithm; maximum lifetime data gathering; optimal continuous solution; wireless sensor networks; Algorithm design and analysis; Approximation algorithms; Approximation methods; Energy consumption; Routing protocols; Wireless communication; Wireless sensor networks; Lifetime; Linear programming; RSM algorithms; WSNs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5623141
  • Filename
    5623141