A deep reinforcement learning approach for online mobile charging scheduling with optimal quality of sensing coverage in wireless rechargeable sensor networks

J Li, H Wang, C Jiang, W Xiao - Ad Hoc Networks, 2024 - Elsevier
Mobile charging provides a new energy replenishment technology for Wireless
Rechargeable Sensor Network (WRSN), where the Mobile Charger (MC) is employed for …

A reinforcement learning based mobile charging sequence scheduling algorithm for optimal sensing coverage in wireless rechargeable sensor networks

J Li, H Wang, W Xiao - Journal of Ambient Intelligence and Humanized …, 2024 - Springer
Mobile charging provides a new way for energy replenishment in the Wireless
Rechargeable Sensor Network (WRSN), where the Mobile Charger (MC) is employed for …

Deep reinforcement learning approach with hybrid action space for mobile charging in wireless rechargeable sensor networks

C Jiang, W Chen, X Chen, S Zhang, W Xiao - Expert Systems with …, 2024 - Elsevier
Mobile charging is feasible to deal with the energy-constrained problem in wireless
rechargeable sensor networks (WRSNs). The mobile chargers (MCs) are usually employed …

A DRL-based Partial Charging Algorithm for Wireless Rechargeable Sensor Networks

J Chen, A Hawbani, X Xu, X Wang, L Zhao… - ACM Transactions on …, 2024 - dl.acm.org
Breakthroughs in Wireless Energy Transfer (WET) technologies have revitalized Wireless
Rechargeable Sensor Networks (WRSNs). However, how to schedule mobile chargers …

A deep reinforcement learning-based on-demand charging algorithm for wireless rechargeable sensor networks

X Cao, W Xu, X Liu, J Peng, T Liu - Ad Hoc Networks, 2021 - Elsevier
Wireless rechargeable sensor networks are widely used in many fields. However, the limited
battery capacity of sensor nodes hinders its development. With the help of wireless energy …

[HTML][HTML] Deep reinforcement learning–based online one-to-multiple charging scheme in wireless rechargeable sensor network

Z Gong, H Wu, Y Feng, N Liu - Sensors, 2023 - mdpi.com
Wireless rechargeable sensor networks (WRSN) have been emerging as an effective
solution to the energy constraint problem of wireless sensor networks (WSN). However, most …

[HTML][HTML] Attention-shared multi-agent actor–critic-based deep reinforcement learning approach for mobile charging dynamic scheduling in wireless rechargeable …

C Jiang, Z Wang, S Chen, J Li, H Wang, J Xiang… - Entropy, 2022 - mdpi.com
The breakthrough of wireless energy transmission (WET) technology has greatly promoted
the wireless rechargeable sensor networks (WRSNs). A promising method to overcome the …

Deep Reinforcement Learning-based Joint Sequence Scheduling and Trajectory Planning in Wireless Rechargeable Sensor Networks

C Jiang, W Chen, Z Wang, W Xiao - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Mobile charging has become a popular and efficient method for replenishing energy. This is
done with a mobile charger (MC) and wireless energy transfer technology (WET), which …

RLR: Joint reinforcement learning and attraction reward for mobile charger in wireless rechargeable sensor networks

C Shang, CY Chang, WH Liao… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Advances in wireless charging technology give great new opportunities for extending the
lifetime of a wireless sensor network (WSN) which is an important infrastructure of IoT …

Reinforcement learning for a novel mobile charging strategy in wireless rechargeable sensor networks

Z Wei, F Liu, Z Lyu, X Ding, L Shi, C Xia - … 2018, Tianjin, China, June 20-22 …, 2018 - Springer
The charging strategy for the mobile charger (MC) has been a hot research topic in wireless
rechargeable sensor networks. We focus on the charging path for the MC, since the MC …