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Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks

In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions...

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Autores principales: Li, Sihao, Kim, Kyeong Soo, Zhang, Linlin, Huan, Xintao, Smith, Jeremy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322639/
https://www.ncbi.nlm.nih.gov/pubmed/35890961
http://dx.doi.org/10.3390/s22145276
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author Li, Sihao
Kim, Kyeong Soo
Zhang, Linlin
Huan, Xintao
Smith, Jeremy
author_facet Li, Sihao
Kim, Kyeong Soo
Zhang, Linlin
Huan, Xintao
Smith, Jeremy
author_sort Li, Sihao
collection PubMed
description In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively.
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spelling pubmed-93226392022-07-27 Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks Li, Sihao Kim, Kyeong Soo Zhang, Linlin Huan, Xintao Smith, Jeremy Sensors (Basel) Article In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively. MDPI 2022-07-14 /pmc/articles/PMC9322639/ /pubmed/35890961 http://dx.doi.org/10.3390/s22145276 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
Li, Sihao
Kim, Kyeong Soo
Zhang, Linlin
Huan, Xintao
Smith, Jeremy
Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title_full Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title_fullStr Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title_full_unstemmed Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title_short Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
title_sort energy-efficient message bundling with delay and synchronization constraints in wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322639/
https://www.ncbi.nlm.nih.gov/pubmed/35890961
http://dx.doi.org/10.3390/s22145276
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