With the development of Wireless Power Transfer (WPT) technology, Wireless Rechargeable Sensor Networks (WRSNs) have become the focus of researchers. Although many researchers have studied the problems of mobile charging in WRSN, they often neglect the differences between sensors. In the actual situation, the utility of different sensors may be different even when they receive the same energy. In this paper, we consider that there are many initial subareas need to be monitored. The different initial subareas have different monitoring utility per unit area, and each sensor covers a circular area. Thus, the entire region can be further divided into more final subareas. The total monitoring utility is the sum of the monitoring utility of the final subareas monitored by sensors. This is the first work to study monitoring-driven mobile charging problem, which considers the differences between different subareas. We model the monitoring-driven mobile charging system and formalize the Monitoring-driven Mobile Charging (MMC) problem. Our goal is to find a traveling loop that does not exceed the energy capacity of the mobile charger, to maximize total monitoring utility. Through area discretization and auxiliary graph construction, we simplify the problem and provide a greedy algorithm to solve it. The simulation results show that the proposed algorithm can outperform comparison algorithms by at most 189.11% in terms of monitoring utility.
| Published in | International Journal of Sensors and Sensor Networks (Volume 11, Issue 2) |
| DOI | 10.11648/j.ijssn.20231102.11 |
| Page(s) | 25-34 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Wireless Charging, Mobile Charging, Monitoring-Driven, Area Discretization, Auxiliary Graph Construction
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APA Style
Wang, Z., Fu, J., Han, L. (2023). Energy Constrained Monitoring-Driven Mobile Charging in Wireless Rechargeable Sensor Networks. International Journal of Sensors and Sensor Networks, 11(2), 25-34. https://doi.org/10.11648/j.ijssn.20231102.11
ACS Style
Wang, Z.; Fu, J.; Han, L. Energy Constrained Monitoring-Driven Mobile Charging in Wireless Rechargeable Sensor Networks. Int. J. Sens. Sens. Netw. 2023, 11(2), 25-34. doi: 10.11648/j.ijssn.20231102.11
AMA Style
Wang Z, Fu J, Han L. Energy Constrained Monitoring-Driven Mobile Charging in Wireless Rechargeable Sensor Networks. Int J Sens Sens Netw. 2023;11(2):25-34. doi: 10.11648/j.ijssn.20231102.11
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Download@article{10.11648/j.ijssn.20231102.11,
author = {Zhiqiang Wang and Jun Fu and Lei Han},
title = {Energy Constrained Monitoring-Driven Mobile Charging in Wireless Rechargeable Sensor Networks},
journal = {International Journal of Sensors and Sensor Networks},
volume = {11},
number = {2},
pages = {25-34},
doi = {10.11648/j.ijssn.20231102.11},
url = {https://doi.org/10.11648/j.ijssn.20231102.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20231102.11},
abstract = {With the development of Wireless Power Transfer (WPT) technology, Wireless Rechargeable Sensor Networks (WRSNs) have become the focus of researchers. Although many researchers have studied the problems of mobile charging in WRSN, they often neglect the differences between sensors. In the actual situation, the utility of different sensors may be different even when they receive the same energy. In this paper, we consider that there are many initial subareas need to be monitored. The different initial subareas have different monitoring utility per unit area, and each sensor covers a circular area. Thus, the entire region can be further divided into more final subareas. The total monitoring utility is the sum of the monitoring utility of the final subareas monitored by sensors. This is the first work to study monitoring-driven mobile charging problem, which considers the differences between different subareas. We model the monitoring-driven mobile charging system and formalize the Monitoring-driven Mobile Charging (MMC) problem. Our goal is to find a traveling loop that does not exceed the energy capacity of the mobile charger, to maximize total monitoring utility. Through area discretization and auxiliary graph construction, we simplify the problem and provide a greedy algorithm to solve it. The simulation results show that the proposed algorithm can outperform comparison algorithms by at most 189.11% in terms of monitoring utility.
},
year = {2023}
}
TY - JOUR T1 - Energy Constrained Monitoring-Driven Mobile Charging in Wireless Rechargeable Sensor Networks AU - Zhiqiang Wang AU - Jun Fu AU - Lei Han Y1 - 2023/11/17 PY - 2023 N1 - https://doi.org/10.11648/j.ijssn.20231102.11 DO - 10.11648/j.ijssn.20231102.11 T2 - International Journal of Sensors and Sensor Networks JF - International Journal of Sensors and Sensor Networks JO - International Journal of Sensors and Sensor Networks SP - 25 EP - 34 PB - Science Publishing Group SN - 2329-1788 UR - https://doi.org/10.11648/j.ijssn.20231102.11 AB - With the development of Wireless Power Transfer (WPT) technology, Wireless Rechargeable Sensor Networks (WRSNs) have become the focus of researchers. Although many researchers have studied the problems of mobile charging in WRSN, they often neglect the differences between sensors. In the actual situation, the utility of different sensors may be different even when they receive the same energy. In this paper, we consider that there are many initial subareas need to be monitored. The different initial subareas have different monitoring utility per unit area, and each sensor covers a circular area. Thus, the entire region can be further divided into more final subareas. The total monitoring utility is the sum of the monitoring utility of the final subareas monitored by sensors. This is the first work to study monitoring-driven mobile charging problem, which considers the differences between different subareas. We model the monitoring-driven mobile charging system and formalize the Monitoring-driven Mobile Charging (MMC) problem. Our goal is to find a traveling loop that does not exceed the energy capacity of the mobile charger, to maximize total monitoring utility. Through area discretization and auxiliary graph construction, we simplify the problem and provide a greedy algorithm to solve it. The simulation results show that the proposed algorithm can outperform comparison algorithms by at most 189.11% in terms of monitoring utility. VL - 11 IS - 2 ER -
Beijing C&W ELECTRONICS (GROUP) Limited Company, Beijing, China
Beijing C&W ELECTRONICS (GROUP) Limited Company, Beijing, China
School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China
