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A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks

To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathe...

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Detalles Bibliográficos
Autores principales: Sha, Chao, Qiu, Jian-mei, Li, Shu-yan, Qiang, Meng-ye, Wang, Ru-chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934349/
https://www.ncbi.nlm.nih.gov/pubmed/27338401
http://dx.doi.org/10.3390/s16060923
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author Sha, Chao
Qiu, Jian-mei
Li, Shu-yan
Qiang, Meng-ye
Wang, Ru-chuan
author_facet Sha, Chao
Qiu, Jian-mei
Li, Shu-yan
Qiang, Meng-ye
Wang, Ru-chuan
author_sort Sha, Chao
collection PubMed
description To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods.
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spelling pubmed-49343492016-07-06 A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks Sha, Chao Qiu, Jian-mei Li, Shu-yan Qiang, Meng-ye Wang, Ru-chuan Sensors (Basel) Article To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods. MDPI 2016-06-21 /pmc/articles/PMC4934349/ /pubmed/27338401 http://dx.doi.org/10.3390/s16060923 Text en © 2016 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
Sha, Chao
Qiu, Jian-mei
Li, Shu-yan
Qiang, Meng-ye
Wang, Ru-chuan
A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title_full A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title_fullStr A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title_full_unstemmed A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title_short A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks
title_sort type of low-latency data gathering method with multi-sink for sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934349/
https://www.ncbi.nlm.nih.gov/pubmed/27338401
http://dx.doi.org/10.3390/s16060923
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