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Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line
Given a set of sensors distributed on the plane and a set of Point of Interests (POIs) on a line segment, a primary task of the mobile wireless sensor network is to schedule covering the POIs by the sensors, such that each POI is monitored by at least one sensor. For balancing the energy consumption...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359190/ https://www.ncbi.nlm.nih.gov/pubmed/30641940 http://dx.doi.org/10.3390/s19020273 |
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author | Huang, Peihuang Zhu, Wenxing Guo, Longkun |
author_facet | Huang, Peihuang Zhu, Wenxing Guo, Longkun |
author_sort | Huang, Peihuang |
collection | PubMed |
description | Given a set of sensors distributed on the plane and a set of Point of Interests (POIs) on a line segment, a primary task of the mobile wireless sensor network is to schedule covering the POIs by the sensors, such that each POI is monitored by at least one sensor. For balancing the energy consumption, we study the min-max line barrier target coverage (LBTC) problem which aims to minimize the maximum movement of the sensors from their original positions to their final positions at which the coverage is composed. We first proved that when the radius of the sensors are non-uniform integers, even 1-dimensional LBTC (1D-LBTC), a special case of LBTC in which the sensors are distributed on the line segment instead of the plane, is [Formula: see text]-hard. The hardness result is interesting, since the continuous version of LBTC to cover a given line segment instead of the POIs is known polynomial solvable. Then we present an exact algorithm for LBTC with uniform radius and sensors distributed on the plane, via solving the decision version of LBTC. We argue that our algorithm runs in time [Formula: see text] and produces an optimal solution to LBTC. The time complexity compares favorably to the state-of-art runtime [Formula: see text] of the continuous version which aims to cover a line barrier instead of the targets. Last but not the least, we carry out numerical experiments to evaluate the practical performance of the algorithms, which demonstrates a practical runtime gain comparing with an optimal algorithm based on integer linear programming. |
format | Online Article Text |
id | pubmed-6359190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63591902019-02-06 Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line Huang, Peihuang Zhu, Wenxing Guo, Longkun Sensors (Basel) Article Given a set of sensors distributed on the plane and a set of Point of Interests (POIs) on a line segment, a primary task of the mobile wireless sensor network is to schedule covering the POIs by the sensors, such that each POI is monitored by at least one sensor. For balancing the energy consumption, we study the min-max line barrier target coverage (LBTC) problem which aims to minimize the maximum movement of the sensors from their original positions to their final positions at which the coverage is composed. We first proved that when the radius of the sensors are non-uniform integers, even 1-dimensional LBTC (1D-LBTC), a special case of LBTC in which the sensors are distributed on the line segment instead of the plane, is [Formula: see text]-hard. The hardness result is interesting, since the continuous version of LBTC to cover a given line segment instead of the POIs is known polynomial solvable. Then we present an exact algorithm for LBTC with uniform radius and sensors distributed on the plane, via solving the decision version of LBTC. We argue that our algorithm runs in time [Formula: see text] and produces an optimal solution to LBTC. The time complexity compares favorably to the state-of-art runtime [Formula: see text] of the continuous version which aims to cover a line barrier instead of the targets. Last but not the least, we carry out numerical experiments to evaluate the practical performance of the algorithms, which demonstrates a practical runtime gain comparing with an optimal algorithm based on integer linear programming. MDPI 2019-01-11 /pmc/articles/PMC6359190/ /pubmed/30641940 http://dx.doi.org/10.3390/s19020273 Text en © 2019 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Huang, Peihuang Zhu, Wenxing Guo, Longkun Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title | Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title_full | Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title_fullStr | Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title_full_unstemmed | Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title_short | Optimizing Movement for Maximizing Lifetime of Mobile Sensors for Covering Targets on a Line |
title_sort | optimizing movement for maximizing lifetime of mobile sensors for covering targets on a line |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359190/ https://www.ncbi.nlm.nih.gov/pubmed/30641940 http://dx.doi.org/10.3390/s19020273 |
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