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Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking

This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersec...

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Autores principales: Huang, Po-Hsian, Chen, Jiann-Liang, Larosa, Yanuarius Teofilus, Chiang, Tsui-Lien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231303/
https://www.ncbi.nlm.nih.gov/pubmed/22163851
http://dx.doi.org/10.3390/s110404358
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author Huang, Po-Hsian
Chen, Jiann-Liang
Larosa, Yanuarius Teofilus
Chiang, Tsui-Lien
author_facet Huang, Po-Hsian
Chen, Jiann-Liang
Larosa, Yanuarius Teofilus
Chiang, Tsui-Lien
author_sort Huang, Po-Hsian
collection PubMed
description This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.
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spelling pubmed-32313032011-12-07 Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking Huang, Po-Hsian Chen, Jiann-Liang Larosa, Yanuarius Teofilus Chiang, Tsui-Lien Sensors (Basel) Article This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies. Molecular Diversity Preservation International (MDPI) 2011-04-13 /pmc/articles/PMC3231303/ /pubmed/22163851 http://dx.doi.org/10.3390/s110404358 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Huang, Po-Hsian
Chen, Jiann-Liang
Larosa, Yanuarius Teofilus
Chiang, Tsui-Lien
Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title_full Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title_fullStr Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title_full_unstemmed Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title_short Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
title_sort estimation of distributed fermat-point location for wireless sensor networking
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231303/
https://www.ncbi.nlm.nih.gov/pubmed/22163851
http://dx.doi.org/10.3390/s110404358
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