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Computing Best Coverage Path In The Presence Of Obstacles In Wireless Sensor Networks

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Computing Best Coverage Path In The Presence Of Obstacles In Wireless Sensor Networks

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dc.contributor.author Basu Roy, Senjuti en_US
dc.date.accessioned 2007-08-23T01:56:02Z
dc.date.available 2007-08-23T01:56:02Z
dc.date.issued 2007-08-23T01:56:02Z
dc.date.submitted April 2007 en_US
dc.identifier.other DISS-1539 en_US
dc.identifier.uri http://hdl.handle.net/10106/85
dc.description.abstract Given a set S = {S1,...,Sn} of n homogeneous wireless sensors deployed in a two dimensional area, a source point s and a destination point t, the least protected point p along a path (s,t) is that point such that the Euclidean distance between p and its closest sensor node Si is maximum. This distance between p and S_{i} is called the Cover value of the path P(s,t). The Best Coverage Path between s and t, denoted as BCP(s,t), is the path that has the minimum cover value. Although there exists efficient algorithms to compute BCP in O(n log n) time, the presence of obstacles inside the two dimensional area has not been addressed in the literature. In this thesis, we consider the problem of computing BCP(s,t) in the presence of m line segment obstacles distributed among n sensors. Because of the presence of obstacles, sensing by sensors can get obstructed and the constructed path may have to detour which pose significant challenges. We propose three algorithms to compute two different variations of the BCP(s; t) problem in the presence of obstacles. In particular, for the case of opaque obstacles, i.e., which obstruct both the sensing as well the computed path, we develop an algorithm that computes BCP(s,t) in $O((m^{2}n^{2} + n^{4})\log(mn+n^{2}))) time. The underlying idea is to leverage the concept of a quartic-time Constrained and Weighted Voronoi diagram among obstacles and creating its dual. For the case of transparent obstacles that cannot obstruct sensing but the computed path has to avoid obstacles, we develop two algorithms that compute BCP(s,t). The first algorithm runs in O(nm^{2}+n^{3}) time using the visibility graph data structure, while the second one is an approximation algorithm and requires O(nm+n^{2})time using spanners of the visibility graph. The approximation factor of the cover value is O nk where k is the stretch factor of the spanner graph. The proofs of correctness of the three proposed algorithms are also presented in this thesis. en_US
dc.description.sponsorship Das, Sajal en_US
dc.language.iso EN en_US
dc.publisher Computer Science & Engineering en_US
dc.title Computing Best Coverage Path In The Presence Of Obstacles In Wireless Sensor Networks en_US
dc.type M.S. en_US
dc.contributor.committeeChair Das, Sajal en_US
dc.degree.department Computer Science & Engineering en_US
dc.degree.discipline Computer Science & Engineering en_US
dc.degree.grantor University of Texas at Arlington en_US
dc.degree.level masters en_US
dc.degree.name M.S. en_US
dc.identifier.externalLink https://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=177
dc.identifier.externalLinkDescription Link to Research Profiles

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