Sensor Network Localization Using Sensor Perturbation

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Sensor Network Localization Using Sensor Perturbation

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Title: Sensor Network Localization Using Sensor Perturbation
Author: Zhu, Yuanchen; Gortler, Steven J.; Thurston, Dylan

Note: Order does not necessarily reflect citation order of authors.

Citation: Zhu, Yuanchen, Steven J. Gortler and Dylan Thurston. 2011. Sensor network localization using sensor perturbation. ACM Transactions on Sensor Networks 7(4): 36.
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Abstract: Sensor network localization is an instance of the NP-Hard graph realization problem. Thus, methods used in practice are not guaranteed to find the correct localization, even if it is uniquely determined by the input distances. In this article, we show the following: if the sensors are allowed to wiggle, giving us perturbed distance data, we can apply a novel algorithm to realize arbitrary Generically Globally Rigid graphs (GGR), or certain vertex subsets in non-GGR graphs whose relative positions are fixed (which include vertex sets of GGR subgraphs). And this strategy works in any dimension. In the language of structural rigidity theory, our approach corresponds to calculating the approximate kernel of a generic stress matrix for the given graph and distance data. To make our algorithm suitable for real-world applications, we also present: (i) various techniques for improving the robustness of the algorithm in the presence of measurement noise; (ii) an algorithm for detecting certain subsets of graph vertices whose relative positions are fixed in any generic realization of the graph and robustly localizing these subsets of vertices, (iii) a strategy for reducing the number of measurements needed by the algorithm. We provide simulation results of our algorithm.
Published Version: doi:10.1145/1921621.1921630
Other Sources: http://cs.harvard.edu/~sjg/papers/bigwiggle.pdf
http://www.people.fas.harvard.edu/~yzhu/doc/perturb-review.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9639959

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  • FAS Scholarly Articles [7106]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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