Sensor Network Localization Using Sensor Perturbation

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Sensor Network Localization Using Sensor Perturbation

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dc.contributor.author Zhu, Yuanchen
dc.contributor.author Gortler, Steven J.
dc.contributor.author Thurston, Dylan
dc.date.accessioned 2012-09-25T19:04:15Z
dc.date.issued 2011
dc.identifier.citation Zhu, Yuanchen, Steven J. Gortler and Dylan Thurston. 2011. Sensor network localization using sensor perturbation. ACM Transactions on Sensor Networks 7(4): 36. en_US
dc.identifier.issn 1550-4859 en_US
dc.identifier.issn 1550-4867 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:9639959
dc.description.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. en_US
dc.description.sponsorship Engineering and Applied Sciences en_US
dc.language.iso en_US en_US
dc.publisher Association for Computing Machinery en_US
dc.relation.isversionof doi:10.1145/1921621.1921630 en_US
dc.relation.hasversion http://cs.harvard.edu/~sjg/papers/bigwiggle.pdf en_US
dc.relation.hasversion http://www.people.fas.harvard.edu/~yzhu/doc/perturb-review.pdf en_US
dash.license OAP
dc.subject algorithm en_US
dc.subject performance en_US
dc.subject theory en_US
dc.subject generic global rigidity en_US
dc.subject globally linked en_US
dc.subject localization en_US
dc.subject rigidity theory en_US
dc.subject sensor networks en_US
dc.subject sensor perturbation en_US
dc.title Sensor Network Localization Using Sensor Perturbation en_US
dc.type Journal Article en_US
dc.description.version Accepted Manuscript en_US
dc.relation.journal ACM Transactions on Sensor Networks en_US
dash.depositing.author Gortler, Steven J.
dc.date.available 2012-09-25T19:04:15Z

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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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