TY - JOUR
T1 - Charging utility maximization in wireless rechargeable sensor networks
AU - Ye, Xiaoguo
AU - Liang, Weifa
N1 - Publisher Copyright:
© 2016, Springer Science+Business Media New York.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - Wireless energy transfer as a promising technology provides an alternative solution to prolong the lifetime of wireless rechargeable sensor networks (WRSNs). In this paper, we study replenishing energy on sensors in a WRSN to shorten energy expiration durations of sensors, by employing a mobile wireless charger to replenish sensors dynamically. We first formulate a novel sensor recharging problem with an objective of maximizing the charging utility of sensors, subject to the total traveling distance of the mobile charger per tour and the charging time window of each to-be-charged sensor. Due to the NP-hardness of the problem, we then propose an approximation algorithm with quasi-polynomial time complexity. In spite of the guaranteed performance ratio of the approximate solution, its time complexity is prohibitively high and may not be feasible in practice. Instead, we devise a fast yet scalable heuristic for the problem in response to dynamic energy consumption of sensors in the network. Furthermore, we also consider the online version of the problem where sensor replenishment is scheduled at every fixed time interval. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithms. Experimental results demonstrate that the proposed algorithms are very promising.
AB - Wireless energy transfer as a promising technology provides an alternative solution to prolong the lifetime of wireless rechargeable sensor networks (WRSNs). In this paper, we study replenishing energy on sensors in a WRSN to shorten energy expiration durations of sensors, by employing a mobile wireless charger to replenish sensors dynamically. We first formulate a novel sensor recharging problem with an objective of maximizing the charging utility of sensors, subject to the total traveling distance of the mobile charger per tour and the charging time window of each to-be-charged sensor. Due to the NP-hardness of the problem, we then propose an approximation algorithm with quasi-polynomial time complexity. In spite of the guaranteed performance ratio of the approximate solution, its time complexity is prohibitively high and may not be feasible in practice. Instead, we devise a fast yet scalable heuristic for the problem in response to dynamic energy consumption of sensors in the network. Furthermore, we also consider the online version of the problem where sensor replenishment is scheduled at every fixed time interval. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithms. Experimental results demonstrate that the proposed algorithms are very promising.
KW - Approximation algorithms
KW - Charging utility
KW - Mobile charging vehicles
KW - Rechargeable sensor networks
KW - Sensor charging scheduling
KW - Wireless energy transfer
UR - http://www.scopus.com/inward/record.url?scp=84964300653&partnerID=8YFLogxK
U2 - 10.1007/s11276-016-1271-6
DO - 10.1007/s11276-016-1271-6
M3 - Article
SN - 1022-0038
VL - 23
SP - 2069
EP - 2081
JO - Wireless Networks
JF - Wireless Networks
IS - 7
ER -