Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means

Version 1 : Received: 19 September 2022 / Approved: 27 September 2022 / Online: 27 September 2022 (02:07:41 CEST)

How to cite: Shan, T.; Wang, Y.; Zhao, C.; Zou, R.; Sun, Y. UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means. Preprints 2022, 2022090402. https://doi.org/10.20944/preprints202209.0402.v1 Shan, T.; Wang, Y.; Zhao, C.; Zou, R.; Sun, Y. UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means. Preprints 2022, 2022090402. https://doi.org/10.20944/preprints202209.0402.v1

Abstract

Aiming at the problem of low charging efficiency caused by the scattered sensor nodes in traditional wireless rechargeable sensor networks (WRSNs), a UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means (UOCS) is proposed. The scheme assumes that the energy consumption of nodes is unpredictable, and only generates charging requests when the energy is lower than a threshold, and performs on-demand responses to nodes that issue charging requests. The scheme combines the characteristics of one-to-one charging of UAVs, the selection and allocation timing of waiting queues and the number of UAVs, and the improved K-means partitioning based on space-time coordination(SPKM), which simplifies the problem of coordinated charging of multiple UAVs and maximizes energy. Using the efficiency and charging success rate, the optimal charging trajectory can be found under the constraint that the node will not starve to death due to power shortage. Finally, a simulation comparison experiment is carried out with the existing UAV charging scheduling strategy. UOCS achieves the optimal node survival rate with low algorithm complexity.

Keywords

Rechargeable Sensor Network; Unmanned Aerial Vehicle; One-to-one Charging; Space-time Collaboration; Optimal Charging Trajectory

Subject

Computer Science and Mathematics, Mathematics

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