Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/72215
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dc.titleWorst and best information exposure paths in wireless sensor networks
dc.contributor.authorWang, B.
dc.contributor.authorChua, K.C.
dc.contributor.authorWang, W.
dc.contributor.authorSrinivasan, V.
dc.date.accessioned2014-06-19T03:32:44Z
dc.date.available2014-06-19T03:32:44Z
dc.date.issued2005
dc.identifier.citationWang, B.,Chua, K.C.,Wang, W.,Srinivasan, V. (2005). Worst and best information exposure paths in wireless sensor networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3794 LNCS : 52-62. ScholarBank@NUS Repository.
dc.identifier.isbn3540308563
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/72215
dc.description.abstractThis paper proposes the concept of information exposure for a point and for a path based on estimation theory. The information exposure of a point is defined as the probability that the absolute value of estimation error is less than some threshold; and the information exposure for a path is the average information exposure of all points along the path. The higher the information exposure, the higher the confidence level that some information of a target is exposed and the better the target is monitored. An approximation algorithm is proposed to solve the problem of finding the worst (best) information exposure path in wireless sensor networks, and its performance is evaluated via simulations. Furthermore, a heuristic for adaptive sensor deployment is proposed to increase the information exposure of the worst information exposure path. © Springer-Verlag Berlin Heidelberg 2005.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume3794 LNCS
dc.description.page52-62
dc.identifier.isiutNOT_IN_WOS
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