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An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks

Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless netw...

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Detalles Bibliográficos
Autores principales: Lei, Chunyang, Bie, Hongxia, Fang, Gengfa, Zhang, Xuekun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721721/
https://www.ncbi.nlm.nih.gov/pubmed/26633421
http://dx.doi.org/10.3390/s151229800
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author Lei, Chunyang
Bie, Hongxia
Fang, Gengfa
Zhang, Xuekun
author_facet Lei, Chunyang
Bie, Hongxia
Fang, Gengfa
Zhang, Xuekun
author_sort Lei, Chunyang
collection PubMed
description Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than [Formula: see text] of the theoretical optimal throughput and [Formula: see text] of fairness index especially in dynamic and dense networks.
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spelling pubmed-47217212016-01-26 An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks Lei, Chunyang Bie, Hongxia Fang, Gengfa Zhang, Xuekun Sensors (Basel) Article Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than [Formula: see text] of the theoretical optimal throughput and [Formula: see text] of fairness index especially in dynamic and dense networks. MDPI 2015-12-03 /pmc/articles/PMC4721721/ /pubmed/26633421 http://dx.doi.org/10.3390/s151229800 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lei, Chunyang
Bie, Hongxia
Fang, Gengfa
Zhang, Xuekun
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title_full An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title_fullStr An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title_full_unstemmed An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title_short An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
title_sort adaptive channel access method for dynamic super dense wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721721/
https://www.ncbi.nlm.nih.gov/pubmed/26633421
http://dx.doi.org/10.3390/s151229800
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