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Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate
As the technology of Internet of Things (IoT) becomes popular, the number of sensor nodes also increases. The network coverage, extensibility, and reliability are also the key points of technical development. To address the challenge of environmental restriction and deployment cost, most sensor node...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9786075/ https://www.ncbi.nlm.nih.gov/pubmed/36560334 http://dx.doi.org/10.3390/s22249963 |
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author | Hung, Chung-Wen Zhuang, Yi-Da Lee, Ching-Hung Wang, Chun-Chieh Yang, Hsi-Hsun |
author_facet | Hung, Chung-Wen Zhuang, Yi-Da Lee, Ching-Hung Wang, Chun-Chieh Yang, Hsi-Hsun |
author_sort | Hung, Chung-Wen |
collection | PubMed |
description | As the technology of Internet of Things (IoT) becomes popular, the number of sensor nodes also increases. The network coverage, extensibility, and reliability are also the key points of technical development. To address the challenge of environmental restriction and deployment cost, most sensor nodes are powered by batteries. Therefore, the low-power consumption becomes an important issue because of the finite value of battery capacity. In addition, significant interference occurs in the environment, thereby complicating reliable wireless communication. This study proposes a fuzzy-based adaptive data rate for the transmission power control in wireless sensor networks to balance the communication quality and power consumption. The error count and error interval perform the inputs of a fuzzy system and the corresponding fuzzy system output is guard that is utilized for limiting the upper bounds of data rate and transmission power. The long-term experimental results are introduced to demonstrate that the control algorithm can overcome environmental interference and obtain low-power performance. The sensor nodes have reliable communication under an ultra-low-power consumption. The experimental results show that the total power consumption of the proposed approach has been improved 73% compared with the system without executing the algorithm and also indicate the Packet Error Rate (PER) is close to 1%. Therefore, the proposed method is suitable for the battery supply IoT system. |
format | Online Article Text |
id | pubmed-9786075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97860752022-12-24 Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate Hung, Chung-Wen Zhuang, Yi-Da Lee, Ching-Hung Wang, Chun-Chieh Yang, Hsi-Hsun Sensors (Basel) Article As the technology of Internet of Things (IoT) becomes popular, the number of sensor nodes also increases. The network coverage, extensibility, and reliability are also the key points of technical development. To address the challenge of environmental restriction and deployment cost, most sensor nodes are powered by batteries. Therefore, the low-power consumption becomes an important issue because of the finite value of battery capacity. In addition, significant interference occurs in the environment, thereby complicating reliable wireless communication. This study proposes a fuzzy-based adaptive data rate for the transmission power control in wireless sensor networks to balance the communication quality and power consumption. The error count and error interval perform the inputs of a fuzzy system and the corresponding fuzzy system output is guard that is utilized for limiting the upper bounds of data rate and transmission power. The long-term experimental results are introduced to demonstrate that the control algorithm can overcome environmental interference and obtain low-power performance. The sensor nodes have reliable communication under an ultra-low-power consumption. The experimental results show that the total power consumption of the proposed approach has been improved 73% compared with the system without executing the algorithm and also indicate the Packet Error Rate (PER) is close to 1%. Therefore, the proposed method is suitable for the battery supply IoT system. MDPI 2022-12-17 /pmc/articles/PMC9786075/ /pubmed/36560334 http://dx.doi.org/10.3390/s22249963 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hung, Chung-Wen Zhuang, Yi-Da Lee, Ching-Hung Wang, Chun-Chieh Yang, Hsi-Hsun Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title | Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title_full | Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title_fullStr | Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title_full_unstemmed | Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title_short | Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate |
title_sort | transmission power control in wireless sensor networks using fuzzy adaptive data rate |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9786075/ https://www.ncbi.nlm.nih.gov/pubmed/36560334 http://dx.doi.org/10.3390/s22249963 |
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