In this study, we investigate the problem of optimizing the charging location and charging time of the mobile charger to ensure the target coverage and ...
Abstract—Target coverage and connectivity are two of the most crucial issues in handling wireless sensor networks. However, maintaining these two factors is ...
Deep Reinforcement Learning-based Charging Algorithm for Target Coverage and Connectivity in WRSNs ... Q-learning-based, Optimized On-demand Charging Algorithm ...
Target coverage and connectivity in WRSNs. We consider the target coverage and connectivity problem (Zhao and Gurusamy, 2008) in the WRSNs' configuration.
Jan 1, 2021 · In this paper, we propose a novel model-free deep reinforcement learning algorithm for the Online Mobile Charging Scheduling with optimal ...
Missing: Connectivity | Show results with:Connectivity
Deep Reinforcement Learning-based Charging Algorithm for Target Coverage and Connectivity in WRSNs. HC Nguyen, MC Dao, TT Nguyen, NK Doan, TH Nguyen, TT ...
Aug 16, 2022 · We address these challenges in this paper by proposing a novel adaptive charging scheme using a deep reinforcement learning (DRL) approach.
Missing: Target Coverage
Apr 1, 2024 · In this paper, we propose a novel model-free deep reinforcement learning algorithm for the Online Mobile Charging Scheduling with optimal Quality of Sensing ...
Missing: Connectivity | Show results with:Connectivity
We propose Fuzzy Q-charging, which uses Q-learning in its charging scheme to guarantee the target coverage and connectivity. Fuzzy Q-charging's reward function ...
We propose a distributed charging algorithm that allows MCs to decide their optimal charging path and charging time.