• DocumentCode
    2795925
  • Title

    Gradient descent approach for secure localization in resource constrained wireless sensor networks

  • Author

    Garg, Ravi ; Varna, Avinash L. ; Wu, Min

  • Author_Institution
    Univ. of Maryland, College Park, MD, USA
  • fYear
    2010
  • fDate
    14-19 March 2010
  • Firstpage
    1854
  • Lastpage
    1857
  • Abstract
    Many sensor network related applications require precise knowledge of the location of constituent nodes. In these applications, it is desirable for the wireless nodes to be able to autonomously determine their locations before they start sensing and transmitting data. Most localization algorithms rely on anchor nodes whose locations are known to determine the positions of the remaining nodes. In an adversarial scenario, some of these anchor nodes could be compromised and used to transmit misleading information aimed at preventing the accurate localization of the remaining sensors. In this paper, a computationally efficient algorithm to determine the location of sensors that can resist such attacks is described. The proposed algorithm combines gradient descent with a selective pruning of inconsistent measurements to achieve good localization accuracy. Simulation results show that the proposed algorithm has performance comparable to existing schemes while requiring less computational resources.
  • Keywords
    gradient methods; wireless sensor networks; computational resources; gradient descent approach; localization algorithms; resource constrained wireless sensor networks; secure localization; Additive noise; Distance measurement; Gaussian noise; Intelligent networks; Intelligent sensors; Military computing; Monitoring; Surveillance; Voting; Wireless sensor networks; Gradient descent; Secure localization; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-4295-9
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2010.5495371
  • Filename
    5495371