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A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks

For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this stu...

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Detalles Bibliográficos
Autores principales: Jiang, Peng, Xu, Yiming, Liu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298759/
https://www.ncbi.nlm.nih.gov/pubmed/28106837
http://dx.doi.org/10.3390/s17010186
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author Jiang, Peng
Xu, Yiming
Liu, Jun
author_facet Jiang, Peng
Xu, Yiming
Liu, Jun
author_sort Jiang, Peng
collection PubMed
description For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime.
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spelling pubmed-52987592017-02-10 A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks Jiang, Peng Xu, Yiming Liu, Jun Sensors (Basel) Article For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime. MDPI 2017-01-19 /pmc/articles/PMC5298759/ /pubmed/28106837 http://dx.doi.org/10.3390/s17010186 Text en © 2017 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
Jiang, Peng
Xu, Yiming
Liu, Jun
A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title_full A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title_fullStr A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title_full_unstemmed A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title_short A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks
title_sort distributed and energy-efficient algorithm for event k-coverage in underwater sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298759/
https://www.ncbi.nlm.nih.gov/pubmed/28106837
http://dx.doi.org/10.3390/s17010186
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