TY - JOUR
T1 - Maximizing Sensor Lifetime via Multi-node Partial-Charging on Sensors
AU - Liu, Jingxiang
AU - Peng, Jian
AU - Xu, Wenzheng
AU - Liang, Weifa
AU - Liu, Tang
AU - Peng, Xi
AU - Xu, Zichuan
AU - Li, Zheng
AU - Jia, Xiaohua
PY - 2023/11
Y1 - 2023/11
N2 - In this paper, we study the employment of a mobile charger to charge lifetime-critical sensors under the multi-node partial-charging model, in which the charger can simultaneously charge the sensors within its charging range and each sensor may be partially charged each time. We notice that existing studies only scheduled the charger to minimize the number of dead sensors, but did not consider the charging scheduling for the sensors that have already run out of their energy, and the dead sensors will be last charged by the mobile charger. Then, their dead durations may be very long. In this paper, we consider not only how to minimize the number of dead sensors but also reduce the dead durations of sensors. To this end, we first formulate a sensor lifetime maximization problem, which is to find a charging tour for a mobile charger to charge sensors, such that the sum of sensor lifetimes is maximized. We then propose a novel 1/3 -approximation algorithm for the problem. We finally evaluate the performance of the proposed algorithm through experiments. Experimental results show that both the average and maximum sensor dead durations by the proposed algorithm are up to 70% shorter than those by existing algorithms. © 2022 IEEE.
AB - In this paper, we study the employment of a mobile charger to charge lifetime-critical sensors under the multi-node partial-charging model, in which the charger can simultaneously charge the sensors within its charging range and each sensor may be partially charged each time. We notice that existing studies only scheduled the charger to minimize the number of dead sensors, but did not consider the charging scheduling for the sensors that have already run out of their energy, and the dead sensors will be last charged by the mobile charger. Then, their dead durations may be very long. In this paper, we consider not only how to minimize the number of dead sensors but also reduce the dead durations of sensors. To this end, we first formulate a sensor lifetime maximization problem, which is to find a charging tour for a mobile charger to charge sensors, such that the sum of sensor lifetimes is maximized. We then propose a novel 1/3 -approximation algorithm for the problem. We finally evaluate the performance of the proposed algorithm through experiments. Experimental results show that both the average and maximum sensor dead durations by the proposed algorithm are up to 70% shorter than those by existing algorithms. © 2022 IEEE.
KW - approximation algorithm
KW - Approximation algorithms
KW - Energy consumption
KW - Forestry
KW - Mobile computing
KW - Monitoring
KW - multi-node charging
KW - partial charging
KW - Schedules
KW - Wireless rechargeable sensor networks
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=85136851558&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85136851558&origin=recordpage
U2 - 10.1109/TMC.2022.3200070
DO - 10.1109/TMC.2022.3200070
M3 - RGC 21 - Publication in refereed journal
SN - 1536-1233
VL - 22
SP - 6571
EP - 6584
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 11
ER -