Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory

On-demand charging scheduling is an important kind of online charging scheduling method in Wireless Rechargeable Sensor Networks (WRSNs). Its dynamism and energy adaptability enables Mobile Chargers (MCs) to adjust charging paths in real-time based on the energy state of the network, which has attra...

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Bibliographic Details
Published in:IEEE journal of the Electron Devices Society 2024-01, Vol.12, p.824-830
Main Author: Wang, Kun
Format: Article
Language:English
Subjects:
Charging
Collaboration
collaborative charging scheduling
Dynamic scheduling
Energy utilization
Game theory
Games
mobile chargers
on-demand charging scheduling
Optimization
Real time
Real-time systems
Scheduling
Sensors
Wireless communication
Wireless rechargeable sensor networks
Wireless sensor networks
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Summary:On-demand charging scheduling is an important kind of online charging scheduling method in Wireless Rechargeable Sensor Networks (WRSNs). Its dynamism and energy adaptability enables Mobile Chargers (MCs) to adjust charging paths in real-time based on the energy state of the network, which has attracted widespread attention since its proposal. While most existing research about it has focused on optimizing the charging utility in the single MC scenario, we aim to optimize on-demand charging scheduling in the scenario of collaborative charging among multiple MCs in this work. Firstly, we have designed a dynamic charging request-sending control mechanism. This mechanism enables sensors to send charging requests according to their remaining lifetime, improving their charging success rate. Secondly, We have modeled the process of MCs' on-demand collaborative charging as a complete information game between MCs. We have designed detailed game rules and proper payoff functions to ensure the survival rate of sensors and improve the Energy Utilization Efficiency(EUE) of the charging process. We have verified the performance of our charging scheduling mechanism through simulations. The simulation results show that our work has good dynamic adaptability, which can effectively improve the EUE of the charging process and reduce the number of sensor failures.
ISSN:2168-6734
2168-6734
DOI:10.1109/JEDS.2023.3342720