Multi-UAV Assisted On-Demand Charging in Dense Wireless Rechargeable Sensor Networks

Wireless rechargeable sensor networks (WRSNs) have emerged as a promising solution to overcome the energy bottleneck in traditional battery-powered sensor networks. However, the uncertain energy demands and dense deployment of sensor nodes pose significant challenges to efficient charging scheduling...

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Bibliographic Details
Published in:IEEE internet of things journal 2024-11, p.1-1
Main Authors: Xiong, Runqun, Chen, Ciyuan, Xu, Jiajun, Dong, Xirui, Pu, Jiahang
Format: Article
Language:English
Subjects:
Autonomous aerial vehicles
Dynamic scheduling
Energy consumption
Energy efficiency
Heuristic algorithms
Inductive charging
On-demand Schedule
Optimization
Resource management
UAV-Assisted Mobile Charging
Wireless communication
Wireless Rechargeable Sensor Networks
Wireless sensor networks
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Summary:Wireless rechargeable sensor networks (WRSNs) have emerged as a promising solution to overcome the energy bottleneck in traditional battery-powered sensor networks. However, the uncertain energy demands and dense deployment of sensor nodes pose significant challenges to efficient charging scheduling in WRSNs. To address these challenges, this paper proposes a novel Multi-UAV assisted On-demand Partial Charging Scheduling (MOPCS) algorithm. MOPCS integrates the advantages of one-to-many charging, partial charging, and dynamic multi-UAV coordination to maximize the network lifetime and energy utilization. The key contributions of this work include a real-time adaptive charging scheduling trigger mechanism, an energy-efficient charging cluster division method, a spatiotemporally balanced task allocation among multiple UAVs, and a hybrid priority-based charging path planning algorithm. Extensive simulations demonstrate that MOPCS significantly outperforms state-of-the-art algorithms in terms of charging request response timeliness, node survival rate, and UAV energy efficiency, especially in dense network deployments. This work provides valuable insights and practical solutions for the design and optimization of UAV-assisted charging scheduling in WRSNs, paving the way for more sustainable and scalable wireless sensor networks in various application scenarios.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3502752