Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1782411266132803584 |
---|---|
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. |
format | Online Article Text |
id | pubmed-4721721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT leichunyang anadaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT biehongxia anadaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT fanggengfa anadaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT zhangxuekun anadaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT leichunyang adaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT biehongxia adaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT fanggengfa adaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks AT zhangxuekun adaptivechannelaccessmethodfordynamicsuperdensewirelesssensornetworks |