TY - GEN
T1 - Profit-driven Wireless Charging Dynamic Scheduling for WRSN in Green IoT
AU - Liu, Silai
AU - Liu, Xilong
AU - Ansari, Nirwan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - With the rapid development of fifth generation (5G) communication technology, Wireless Rechargeable Sensor Networks (WRSNs) have gained attention. Wireless Power Transfer (WPT) enables WRSNs to play important roles in Internet of Things (IoT) applications like smart cities, smart farms and intelligent factories. In these scenarios, in order to save on-grid energy and protect environment, a Green Base Station (GBS) is leveraged to first harvest green energy and then wirelessly power the surrounding sensors in WRSNs by WPT. Most related works focus on maximizing the Green Energy Utilization (GEU) in WPT but overlook reducing nodes' waiting time for energy replenishment, which affects Quality of Service (QoS) and the wireless charging service provider's profit in terms of losing customers. Hence, in this paper, we first propose a novel pricing model that reflects waiting time to maximize the provider's profit. The charging profit maximization problem is formulated as an optimization problem, which is NP-hard, and solved by a heuristic algorithm called Dynamic Scheduling (DS) that considers both waiting time and GEU. Finally, we validate the performance of the proposed algorithm through extensive simulations.
AB - With the rapid development of fifth generation (5G) communication technology, Wireless Rechargeable Sensor Networks (WRSNs) have gained attention. Wireless Power Transfer (WPT) enables WRSNs to play important roles in Internet of Things (IoT) applications like smart cities, smart farms and intelligent factories. In these scenarios, in order to save on-grid energy and protect environment, a Green Base Station (GBS) is leveraged to first harvest green energy and then wirelessly power the surrounding sensors in WRSNs by WPT. Most related works focus on maximizing the Green Energy Utilization (GEU) in WPT but overlook reducing nodes' waiting time for energy replenishment, which affects Quality of Service (QoS) and the wireless charging service provider's profit in terms of losing customers. Hence, in this paper, we first propose a novel pricing model that reflects waiting time to maximize the provider's profit. The charging profit maximization problem is formulated as an optimization problem, which is NP-hard, and solved by a heuristic algorithm called Dynamic Scheduling (DS) that considers both waiting time and GEU. Finally, we validate the performance of the proposed algorithm through extensive simulations.
KW - Dynamic scheduling algorithm
KW - Green energy utilization
KW - Green loT
KW - QoS
UR - http://www.scopus.com/inward/record.url?scp=85186095143&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85186095143&partnerID=8YFLogxK
U2 - 10.1109/ICCT59356.2023.10419461
DO - 10.1109/ICCT59356.2023.10419461
M3 - Conference contribution
AN - SCOPUS:85186095143
T3 - International Conference on Communication Technology Proceedings, ICCT
SP - 1450
EP - 1455
BT - 2023 IEEE 23rd International Conference on Communication Technology
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Communication Technology, ICCT 2023
Y2 - 20 October 2023 through 22 October 2023
ER -