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Smart city article details
| Title | Profit-Driven Wireless Charging Dynamic Scheduling For Wrsn In Green Iot |
|---|---|
| ID_Doc | 43343 |
| Authors | Liu S.; Liu X.; Ansari N. |
| Year | 2023 |
| Published | International Conference on Communication Technology Proceedings, ICCT |
| DOI | http://dx.doi.org/10.1109/ICCT59356.2023.10419461 |
| Abstract | 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. © 2023 IEEE. |
| Author Keywords | Dynamic scheduling algorithm; Green energy utilization; Green loT; QoS |
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