您现在的位置:首页 > 学术研究 > 论文发表 > A Novel Mobile Charging Planning Method based on Swarm Reinforcement Learning in Wireless Sensor Networks
A Novel Mobile Charging Planning Method based on Swarm Reinforcement Learning in Wireless Sensor Networks
[发布时间:2023-03-28  阅读次数: 311]

作者: Zengwei Lyu, Pengfei Li,  Zhenchun Wei,  Juan Xu,  Lei Shi

发表刊物:International Journal of Sensor Networks

年份:October 2023

摘要:In order to solve the problem of energy supplement in large-scale wireless sensor networks (WSNs), this paper investigates the charging planning problem by introduced multiple wireless charger equipment (WCE). We first established the optimisation model of the multi-WCE charging planning problem to minimise the total charging time and the total energy consumption of the WCE. Then, the problem is modelled as a reinforcement learning process, and the time step, state space, action space, state transfer function and reward function are designed. Moreover, based on the idea of swarm intelligence optimisation method, a multi-learners&39; strategy is introduced to enable multi-learners to parallel learning, so as to accelerate the solution finding speed. Therefore, a discrete firework Q-learning algorithm is proposed to solve the problem. Experiments show that the proposed algorithm outperforms the baseline algorithms in different network scales.

参考文献拷贝字段:Zengwei Lyu, Pengfei Li,  Zhenchun Wei, Juan Xu, Lei Shi. A Novel Mobile Charging Planning Method based on Swarm Reinforcement Learning in Wireless Sensor Networks[J]. International Journal of Sensor Networks, 2023, 41(3): 176-188.