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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2024-01-01
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| Series: | IEEE Journal of the Electron Devices Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10356616/ |
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| author | Kun Wang |
| author_facet | Kun Wang |
| author_sort | Kun Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ca84c97a6be74bc2a13e430af92d0c19 |
| institution | Kabale University |
| issn | 2168-6734 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of the Electron Devices Society |
| spelling | doaj-art-ca84c97a6be74bc2a13e430af92d0c192025-01-29T00:00:28ZengIEEEIEEE Journal of the Electron Devices Society2168-67342024-01-011282483010.1109/JEDS.2023.334272010356616Dynamic On-Demand Collaborative Charging Scheduling Based on Game TheoryKun Wang0https://orcid.org/0000-0003-0419-3586School of Government Management, Liaoning Normal University, Dalian, ChinaOn-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.https://ieeexplore.ieee.org/document/10356616/Wireless rechargeable sensor networksgame theoryon-demand charging schedulingcollaborative charging schedulingmobile chargers |
| spellingShingle | Kun Wang Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory IEEE Journal of the Electron Devices Society Wireless rechargeable sensor networks game theory on-demand charging scheduling collaborative charging scheduling mobile chargers |
| title | Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory |
| title_full | Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory |
| title_fullStr | Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory |
| title_full_unstemmed | Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory |
| title_short | Dynamic On-Demand Collaborative Charging Scheduling Based on Game Theory |
| title_sort | dynamic on demand collaborative charging scheduling based on game theory |
| topic | Wireless rechargeable sensor networks game theory on-demand charging scheduling collaborative charging scheduling mobile chargers |
| url | https://ieeexplore.ieee.org/document/10356616/ |
| work_keys_str_mv | AT kunwang dynamicondemandcollaborativechargingschedulingbasedongametheory |