The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Les réseaux de capteurs sans fil assurent une surveillance à long terme de l'environnement, mais les capteurs sont alimentés par de petites batteries. Utilisant un chargeur mobile (MC) reconstituer l’énergie des capteurs est une solution prometteuse pour prolonger leur durée d’utilisation. De nombreuses approches ont été développées pour trouver la trajectoire de déplacement du MC, et elles supposent que les capteurs ont une trajectoire fixe. taux de détection (SR) et préfèrent charger complètement les capteurs. En pratique, les capteurs peuvent ajuster leurs SR de manière adaptative pour répondre aux demandes des applications ou économiser de l'énergie. En outre, en raison de la politique de charge complète, certains capteurs à faible consommation d'énergie peuvent mettre longtemps à attendre le service du MC. Ainsi, le document formule une problème de chemin et de charge (P&C), qui demande comment envoyer le MC visiter les capteurs dotés de SR adaptatifs et décider de leur temps de charge, de manière à maximiser la capacité de survie et le débit des capteurs. Ensuite, nous proposons un algorithme efficace de planification IARD (EPCS), qui construit le chemin le plus court pour visiter chaque capteur. Pour que le MC se déplace rapidement pour charger les capteurs proches de la mort, certains capteurs disposant de suffisamment d'énergie sont exclus du chemin. De plus, EPCS adopte un mécanisme de charge flottant basé sur le ratio de capteurs fonctionnels et leur épuisement d'énergie. Les résultats de la simulation vérifient qu'EPCS peut améliorer considérablement la capacité de survie et le débit des capteurs.
You-Chiun WANG
National Sun Yat-sen University
Yu-Cheng BAI
National Sun Yat-sen University
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You-Chiun WANG, Yu-Cheng BAI, "Efficient Schedule of Path and Charge for a Mobile Charger to Improve Survivability and Throughput of Sensors with Adaptive Sensing Rates" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 11, pp. 1380-1389, November 2022, doi: 10.1587/transcom.2021TMP0001.
Abstract: Wireless sensor networks provide long-term monitoring of the environment, but sensors are powered by small batteries. Using a mobile charger (MC) to replenish energy of sensors is one promising solution to prolong their usage time. Many approaches have been developed to find the MC's moving path, and they assume that sensors have a fixed sensing rate (SR) and prefer to fully charge sensors. In practice, sensors can adaptively adjust their SRs to meet application demands or save energy. Besides, due to the fully charging policy, some sensors with low energy may take long to wait for the MC's service. Thus, the paper formulates a path and charge (P&C) problem, which asks how to dispatch the MC to visit sensors with adaptive SRs and decide their charging time, such that both survivability and throughput of sensors can be maximized. Then, we propose an efficient P&C scheduling (EPCS) algorithm, which builds the shortest path to visit each sensor. To make the MC fast move to charge the sensors near death, some sensors with enough energy are excluded from the path. Moreover, EPCS adopts a floating charging mechanism based on the ratio of workable sensors and their energy depletion. Simulation results verify that EPCS can significantly improve the survivability and throughput of sensors.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021TMP0001/_p
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@ARTICLE{e105-b_11_1380,
author={You-Chiun WANG, Yu-Cheng BAI, },
journal={IEICE TRANSACTIONS on Communications},
title={Efficient Schedule of Path and Charge for a Mobile Charger to Improve Survivability and Throughput of Sensors with Adaptive Sensing Rates},
year={2022},
volume={E105-B},
number={11},
pages={1380-1389},
abstract={Wireless sensor networks provide long-term monitoring of the environment, but sensors are powered by small batteries. Using a mobile charger (MC) to replenish energy of sensors is one promising solution to prolong their usage time. Many approaches have been developed to find the MC's moving path, and they assume that sensors have a fixed sensing rate (SR) and prefer to fully charge sensors. In practice, sensors can adaptively adjust their SRs to meet application demands or save energy. Besides, due to the fully charging policy, some sensors with low energy may take long to wait for the MC's service. Thus, the paper formulates a path and charge (P&C) problem, which asks how to dispatch the MC to visit sensors with adaptive SRs and decide their charging time, such that both survivability and throughput of sensors can be maximized. Then, we propose an efficient P&C scheduling (EPCS) algorithm, which builds the shortest path to visit each sensor. To make the MC fast move to charge the sensors near death, some sensors with enough energy are excluded from the path. Moreover, EPCS adopts a floating charging mechanism based on the ratio of workable sensors and their energy depletion. Simulation results verify that EPCS can significantly improve the survivability and throughput of sensors.},
keywords={},
doi={10.1587/transcom.2021TMP0001},
ISSN={1745-1345},
month={November},}
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TY - JOUR
TI - Efficient Schedule of Path and Charge for a Mobile Charger to Improve Survivability and Throughput of Sensors with Adaptive Sensing Rates
T2 - IEICE TRANSACTIONS on Communications
SP - 1380
EP - 1389
AU - You-Chiun WANG
AU - Yu-Cheng BAI
PY - 2022
DO - 10.1587/transcom.2021TMP0001
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2022
AB - Wireless sensor networks provide long-term monitoring of the environment, but sensors are powered by small batteries. Using a mobile charger (MC) to replenish energy of sensors is one promising solution to prolong their usage time. Many approaches have been developed to find the MC's moving path, and they assume that sensors have a fixed sensing rate (SR) and prefer to fully charge sensors. In practice, sensors can adaptively adjust their SRs to meet application demands or save energy. Besides, due to the fully charging policy, some sensors with low energy may take long to wait for the MC's service. Thus, the paper formulates a path and charge (P&C) problem, which asks how to dispatch the MC to visit sensors with adaptive SRs and decide their charging time, such that both survivability and throughput of sensors can be maximized. Then, we propose an efficient P&C scheduling (EPCS) algorithm, which builds the shortest path to visit each sensor. To make the MC fast move to charge the sensors near death, some sensors with enough energy are excluded from the path. Moreover, EPCS adopts a floating charging mechanism based on the ratio of workable sensors and their energy depletion. Simulation results verify that EPCS can significantly improve the survivability and throughput of sensors.
ER -