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A Fast Neighbor Discovery Algorithm in WSNs†

With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure tha...

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Autores principales: Wei, Liangxiong, Sun, Weijie, Chen, Haixiang, Yuan, Ping, Yin, Feng, Luo, Qian, Chen, Yanru, Chen, Liangyin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210503/
https://www.ncbi.nlm.nih.gov/pubmed/30282944
http://dx.doi.org/10.3390/s18103319
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author Wei, Liangxiong
Sun, Weijie
Chen, Haixiang
Yuan, Ping
Yin, Feng
Luo, Qian
Chen, Yanru
Chen, Liangyin
author_facet Wei, Liangxiong
Sun, Weijie
Chen, Haixiang
Yuan, Ping
Yin, Feng
Luo, Qian
Chen, Yanru
Chen, Liangyin
author_sort Wei, Liangxiong
collection PubMed
description With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure that successful discovery can be obtained within a given period of time, but the average discovery delay is long. It is difficult to meet the need for rapid discovery in mobile low duty cycle environments. In addition, with the rapid development of IoT, the node densities of many WSNs greatly increase. In such scenarios, existing neighbor discovery methods fail to satisfy the requirement in terms of discovery latency under the condition of the same energy consumption. This paper proposes a group-based fast neighbor discovery algorithm (GBFA) to address the issues. By carrying neighbor information in beacon packet, the node knows in advance some potential neighbors. It selects more energy efficient potential neighbors and proactively makes nodes wake up to verify whether these potential neighbors are true neighbors, thereby speeding up neighbor discovery, improving energy utilization efficiency and decreasing network communication load. The evaluation results indicate that, compared with other methods, GBFA decreases the average discovery latency up to [Formula: see text] at the same energy budget.
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spelling pubmed-62105032018-11-02 A Fast Neighbor Discovery Algorithm in WSNs† Wei, Liangxiong Sun, Weijie Chen, Haixiang Yuan, Ping Yin, Feng Luo, Qian Chen, Yanru Chen, Liangyin Sensors (Basel) Article With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure that successful discovery can be obtained within a given period of time, but the average discovery delay is long. It is difficult to meet the need for rapid discovery in mobile low duty cycle environments. In addition, with the rapid development of IoT, the node densities of many WSNs greatly increase. In such scenarios, existing neighbor discovery methods fail to satisfy the requirement in terms of discovery latency under the condition of the same energy consumption. This paper proposes a group-based fast neighbor discovery algorithm (GBFA) to address the issues. By carrying neighbor information in beacon packet, the node knows in advance some potential neighbors. It selects more energy efficient potential neighbors and proactively makes nodes wake up to verify whether these potential neighbors are true neighbors, thereby speeding up neighbor discovery, improving energy utilization efficiency and decreasing network communication load. The evaluation results indicate that, compared with other methods, GBFA decreases the average discovery latency up to [Formula: see text] at the same energy budget. MDPI 2018-10-03 /pmc/articles/PMC6210503/ /pubmed/30282944 http://dx.doi.org/10.3390/s18103319 Text en © 2018 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
Wei, Liangxiong
Sun, Weijie
Chen, Haixiang
Yuan, Ping
Yin, Feng
Luo, Qian
Chen, Yanru
Chen, Liangyin
A Fast Neighbor Discovery Algorithm in WSNs†
title A Fast Neighbor Discovery Algorithm in WSNs†
title_full A Fast Neighbor Discovery Algorithm in WSNs†
title_fullStr A Fast Neighbor Discovery Algorithm in WSNs†
title_full_unstemmed A Fast Neighbor Discovery Algorithm in WSNs†
title_short A Fast Neighbor Discovery Algorithm in WSNs†
title_sort fast neighbor discovery algorithm in wsns†
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210503/
https://www.ncbi.nlm.nih.gov/pubmed/30282944
http://dx.doi.org/10.3390/s18103319
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