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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
As redes de sensores sem fio fornecem monitoramento do ambiente a longo prazo, mas os sensores são alimentados por pequenas baterias. Usando um carregador móvel (MC) reabastecer a energia dos sensores é uma solução promissora para prolongar seu tempo de uso. Muitas abordagens foram desenvolvidas para encontrar o caminho do movimento do MC e assumem que os sensores têm uma distância fixa. taxa de detecção (SR) e prefira carregar totalmente os sensores. Na prática, os sensores podem ajustar seus SRs de forma adaptativa para atender às demandas da aplicação ou economizar energia. Além disso, devido à política de carga total, alguns sensores com baixa energia podem demorar muito para aguardar o atendimento do MC. Assim, o artigo formula uma problema de caminho e carga (P&C), que pergunta como despachar o MC para visitar sensores com SRs adaptativos e decidir seu tempo de carregamento, de modo que tanto a capacidade de sobrevivência quanto o rendimento dos sensores possam ser maximizados. Em seguida, propomos uma algoritmo eficiente de agendamento de P&C (EPCS), que constrói o caminho mais curto para visitar cada sensor. Para fazer o MC se mover rapidamente para carregar os sensores perto da morte, alguns sensores com energia suficiente são excluídos do caminho. Além disso, o EPCS adota um mecanismo de carregamento flutuante baseado na proporção de sensores viáveis e no seu esgotamento de energia. Os resultados da simulação verificam que o EPCS pode melhorar significativamente a capacidade de sobrevivência e o rendimento dos sensores.
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 -