Minimizing charging task time of WRSN assisted with multiple MUVs and laser-charged UAVs

Abstract

This paper investigates the framework of wireless rechargeable sensor network (WRSN) assisted by multiple mobile unmanned vehicles (MUVs) and laser-charged unmanned aerial vehicles (UAVs). On the basis of framework, we cooperatively investigate the trajectory optimization of multi-UAVs and multi-MUVs for charging WRSN (TOUM) problem, whose goal aims at designing the optimal travel plan of UAVs and MUVs cooperatively to charge WRSN such that the remaining energy of each sensor in WRSN is greater than or equal to the threshold and the time consumption of UAV that takes the most time of all UAVs is minimized. The TOUM problem is proved NP-hard. To solve the TOUM problem, we first investigate the multiple UAVs-based TSP (MUTSP) problem to balance the charging tasks assigned to every UAV. Then, based on the MUTSP problem, we propose the TOUM algorithm (TOUMA) to design the detailed travel plan of UAVs and MUVs. We also present an algorithm named TOUM-DQN to make intelligent decisions about the travel plan of UAVs and MUVs by extracting valuable information from the network. The effectiveness of proposed algorithms is verified through extensive simulation experiments. The results demonstrate that the TOUMA algorithm outperforms the solar charging method, the base station charging method, and the TOUM-DQN algorithm in terms of time efficiency. Simultaneously, the experimental results show that the execution time of TOUM-DQN algorithm is significantly lower than TOUMA algorithm.

Keywords

Wireless rechargeable sensor network / Unmanned aerial vehicles / Mobile unmanned vehicle / Trajectory optimization / Deep Q-network

CRediT authorship contribution statement

Jian Zhang: Methodology, Software, Validation, Formal analysis, Writing - original draft, Visualization. Chuanwen Luo: Conceptualization, Supervision, Project administration, Funding acquisition. Ning Liu: Investigation, Resources, Data curation, Writing - review & editing. Yi Hong: Methodology, Validation, Formal analysis. Zhibo Chen: Investigation, Resources, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

A preliminary version Luo et al. of this paper appeared in The 16th IEEE International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage (IEEE SpaCCS 2023). This research was funded by the National Natural Science Foundation of China (62202054), and the Young Elite Scientists Sponsorship Program (CAST 2023ONRC001.)

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