TY - JOUR
T1 - Particle swarm optimization for charger deployment in wireless rechargeable sensor networks
AU - Jiang, Jehn Ruey
AU - Chen, Yen Chung
AU - Lin, Ting Yu
N1 - Publisher Copyright:
© 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - In Wireless Rechargeable Sensor Networks (WRSNs), wireless chargers can recharge batteries of sensor nodes so that they can operate sustainably. Since wireless chargers are costly and have limited charging distances and angles, how to apply as few as possible chargers to cover all sensor nodes and satisfy their energy requirements is thus an important and challenging problem. This paper introduces the PSCD (Particle Swarm Charger Deployment) algorithm and the IPSCD (Improved PSCD) algorithm using the Particle Swarm Optimization (PSO) concept to nearly optimize WRSN charger deployment. PSCD and IPSCD estimate charging efficiency according to the distance and angle between chargers and sensor nodes. They then, on the basis of PSO, utilize the local optimum and the global optimum to adjust locations and antenna orientations of chargers to make WRSNs sustainable. We perform experiments using practical wireless chargers to obtain charging efficiency data. Based on the data, PSCD and IPSCD are simulated for obtaining the best parameter setting, and compared with two related greedy algorithms to show their superiority.
AB - In Wireless Rechargeable Sensor Networks (WRSNs), wireless chargers can recharge batteries of sensor nodes so that they can operate sustainably. Since wireless chargers are costly and have limited charging distances and angles, how to apply as few as possible chargers to cover all sensor nodes and satisfy their energy requirements is thus an important and challenging problem. This paper introduces the PSCD (Particle Swarm Charger Deployment) algorithm and the IPSCD (Improved PSCD) algorithm using the Particle Swarm Optimization (PSO) concept to nearly optimize WRSN charger deployment. PSCD and IPSCD estimate charging efficiency according to the distance and angle between chargers and sensor nodes. They then, on the basis of PSO, utilize the local optimum and the global optimum to adjust locations and antenna orientations of chargers to make WRSNs sustainable. We perform experiments using practical wireless chargers to obtain charging efficiency data. Based on the data, PSCD and IPSCD are simulated for obtaining the best parameter setting, and compared with two related greedy algorithms to show their superiority.
KW - Wireless rechargeable sensor network
KW - particle swarm optimization
KW - sustainability
KW - wireless charger deployment
UR - http://www.scopus.com/inward/record.url?scp=85041125640&partnerID=8YFLogxK
U2 - 10.1080/17445760.2018.1426761
DO - 10.1080/17445760.2018.1426761
M3 - 期刊論文
AN - SCOPUS:85041125640
SN - 1744-5760
VL - 36
SP - 652
EP - 667
JO - International Journal of Parallel, Emergent and Distributed Systems
JF - International Journal of Parallel, Emergent and Distributed Systems
IS - 6
ER -