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
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