TY - GEN
T1 - Practical Concurrent Wireless Charging Scheduling for Sensor Networks
AU - Guo, Peng
AU - Liu, Xuefeng
AU - Tang, Tingfang
AU - Tang, Shaojie
AU - Cao, Jiannong
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/8
Y1 - 2016/8/8
N2 - In complex terrain where mobile chargers hardly move around, a feasible solution to charge wireless sensor networks (WSNs) is using multiple fixed chargers to charge WSNs concurrently with relative long distance. Due to the radio interference in the concurrent charging, it is needed to schedule the chargers so as to facilitate each sensor node to harvest sufficient energy quickly. The challenge lies that each charger's charging utility cannot be calculated (or even defined) independently due to the nonlinear superposition charging effect caused by the radio interference. In this paper, we model the concurrent radio charging, and formulate the concurrent charging scheduling problem (CCSP) whose objective is to design a scheduling algorithm for the chargers so as to minimize the time spent on charging each sensor node with at least energy E. We prove that CCSP is NP-hard, and propose a greedy algorithm based on submodular set cover problem. We also propose a genetic algorithm for CCSP. Simulation results show that the performance of the greedy CCSP algorithm is comparable to that of the genetic algorithm.
AB - In complex terrain where mobile chargers hardly move around, a feasible solution to charge wireless sensor networks (WSNs) is using multiple fixed chargers to charge WSNs concurrently with relative long distance. Due to the radio interference in the concurrent charging, it is needed to schedule the chargers so as to facilitate each sensor node to harvest sufficient energy quickly. The challenge lies that each charger's charging utility cannot be calculated (or even defined) independently due to the nonlinear superposition charging effect caused by the radio interference. In this paper, we model the concurrent radio charging, and formulate the concurrent charging scheduling problem (CCSP) whose objective is to design a scheduling algorithm for the chargers so as to minimize the time spent on charging each sensor node with at least energy E. We prove that CCSP is NP-hard, and propose a greedy algorithm based on submodular set cover problem. We also propose a genetic algorithm for CCSP. Simulation results show that the performance of the greedy CCSP algorithm is comparable to that of the genetic algorithm.
KW - Wireless Sensor Network (WSN)
KW - nonlinear superposition charging effect
KW - scheduling
KW - submodular set cover
KW - wireless charging
UR - https://www.scopus.com/pages/publications/84985991732
U2 - 10.1109/ICDCS.2016.33
DO - 10.1109/ICDCS.2016.33
M3 - 会议稿件
AN - SCOPUS:84985991732
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 741
EP - 742
BT - Proceedings - 2016 IEEE 36th International Conference on Distributed Computing Systems, ICDCS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Conference on Distributed Computing Systems, ICDCS 2016
Y2 - 27 June 2016 through 30 June 2016
ER -