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An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks
In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given fre...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231220/ https://www.ncbi.nlm.nih.gov/pubmed/22163643 http://dx.doi.org/10.3390/s100908101 |
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author | Lin, Frank Yeong-Sung Lee, Cheng-Ta |
author_facet | Lin, Frank Yeong-Sung Lee, Cheng-Ta |
author_sort | Lin, Frank Yeong-Sung |
collection | PubMed |
description | In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time. |
format | Online Article Text |
id | pubmed-3231220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32312202011-12-07 An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks Lin, Frank Yeong-Sung Lee, Cheng-Ta Sensors (Basel) Article In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time. Molecular Diversity Preservation International (MDPI) 2010-08-27 /pmc/articles/PMC3231220/ /pubmed/22163643 http://dx.doi.org/10.3390/s100908101 Text en © 2010 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 Lin, Frank Yeong-Sung Lee, Cheng-Ta An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title | An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title_full | An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title_fullStr | An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title_full_unstemmed | An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title_short | An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks |
title_sort | efficient lagrangean relaxation-based object tracking algorithm in wireless sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231220/ https://www.ncbi.nlm.nih.gov/pubmed/22163643 http://dx.doi.org/10.3390/s100908101 |
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