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An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic
As the reference communication standard of wireless sensor networks (WSNs), the IEEE 802.15.4 standard has been adopted in various WSN-based applications. In many of these applications, one of the most common traffic pattern types is a periodic traffic patterns, however, the majority of existing ana...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349516/ https://www.ncbi.nlm.nih.gov/pubmed/32545668 http://dx.doi.org/10.3390/s20123350 |
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author | Wang, Yipeng Yang, Wei Han, Ruisong Xu, Linsen Zhao, Haojiang |
author_facet | Wang, Yipeng Yang, Wei Han, Ruisong Xu, Linsen Zhao, Haojiang |
author_sort | Wang, Yipeng |
collection | PubMed |
description | As the reference communication standard of wireless sensor networks (WSNs), the IEEE 802.15.4 standard has been adopted in various WSN-based applications. In many of these applications, one of the most common traffic pattern types is a periodic traffic patterns, however, the majority of existing analytical models target either saturated or unsaturated network traffic patterns. Furthermore, few of them can be directly extended to the periodic traffic scenario, since periodic traffic brings unstable load status to sensor nodes. To better characterize the WSNs with periodic traffic, we propose an accurate and scalable analytical framework for the IEEE 802.15.4 MAC protocol. By formulating the relationship between clear channel assessment (CCA) and its successful probability from the perspective of channel state and node state, single node’s behavior and whole network’s performance under different network scales and traffic loads can be derived. Extensive simulations are conducted to validate the proposed framework in terms of both local statistics and overall statistics, and the results show that the model can represent the actual behavior and the real performance of both single node and whole network. Besides, as the simplified version of double CCAs mode (DS mode), single CCA mode (SS mode), is also analyzed with simple modifications on the proposed analytical framework. Combining the analytical framework with simulation results, the applicable network scenarios of two modes are also demonstrated respectively. Finally, an approximate distribution of one data packet’s backoff duration is proposed. With this approximate distribution, a conservative estimation of data packet’s average transmission latency in networks with given configurations can be easily carried out. |
format | Online Article Text |
id | pubmed-7349516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73495162020-07-14 An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic Wang, Yipeng Yang, Wei Han, Ruisong Xu, Linsen Zhao, Haojiang Sensors (Basel) Article As the reference communication standard of wireless sensor networks (WSNs), the IEEE 802.15.4 standard has been adopted in various WSN-based applications. In many of these applications, one of the most common traffic pattern types is a periodic traffic patterns, however, the majority of existing analytical models target either saturated or unsaturated network traffic patterns. Furthermore, few of them can be directly extended to the periodic traffic scenario, since periodic traffic brings unstable load status to sensor nodes. To better characterize the WSNs with periodic traffic, we propose an accurate and scalable analytical framework for the IEEE 802.15.4 MAC protocol. By formulating the relationship between clear channel assessment (CCA) and its successful probability from the perspective of channel state and node state, single node’s behavior and whole network’s performance under different network scales and traffic loads can be derived. Extensive simulations are conducted to validate the proposed framework in terms of both local statistics and overall statistics, and the results show that the model can represent the actual behavior and the real performance of both single node and whole network. Besides, as the simplified version of double CCAs mode (DS mode), single CCA mode (SS mode), is also analyzed with simple modifications on the proposed analytical framework. Combining the analytical framework with simulation results, the applicable network scenarios of two modes are also demonstrated respectively. Finally, an approximate distribution of one data packet’s backoff duration is proposed. With this approximate distribution, a conservative estimation of data packet’s average transmission latency in networks with given configurations can be easily carried out. MDPI 2020-06-12 /pmc/articles/PMC7349516/ /pubmed/32545668 http://dx.doi.org/10.3390/s20123350 Text en © 2020 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 Wang, Yipeng Yang, Wei Han, Ruisong Xu, Linsen Zhao, Haojiang An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title | An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title_full | An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title_fullStr | An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title_full_unstemmed | An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title_short | An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic |
title_sort | analytical framework for the ieee 802.15.4 mac layer protocol under periodic traffic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349516/ https://www.ncbi.nlm.nih.gov/pubmed/32545668 http://dx.doi.org/10.3390/s20123350 |
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