{"title":"基于无人机的无线传感器网络充电非合作定价策略","authors":"Ajay Kumar Gupta;Manav R. Bhatnagar","doi":"10.1109/TGCN.2024.3434603","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks are essential for monitoring, control, and surveillance operations, but the limited battery capacity of wireless rechargeable sensor nodes (WRSNs) poses a significant challenge. To address this, on-demand charging from an external power source is fundamental for the effective operation of energy-critical WRSNs. In this article, the wireless charging of the independent WRSNs in a network is modeled as a service in a common competitive market, where multiple charging service providers (CSPs) indulge in a pricing war to maximize their profits by achieving fair market share based on area division. A competitive market scenario is considered where multiple non-cooperative CSPs are strategically located at their fixed grounded stations, and the most economical CSP gets requested from a WRSN for charging. The CSPs are associated with UAV-enabled chargers (UAVEC), which are dispatched to the concerned WRSNs with known positions and recharged wirelessly in a time-bound manner. This paper study a suitable pricing strategy for on-demand charging of the WRSNs in a competitive market scenario; and investigate the existence of Nash equilibrium (NE) for prices and profits of CSPs using a game-theoretic approach. The closed-form expressions of NE conditions and the CSP selection criterion for WRSNs are obtained, and the results are verified through simulations.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 2","pages":"459-470"},"PeriodicalIF":5.3000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Non-Cooperative Pricing Strategy for UAV-Enabled Charging of Wireless Sensor Network\",\"authors\":\"Ajay Kumar Gupta;Manav R. Bhatnagar\",\"doi\":\"10.1109/TGCN.2024.3434603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless sensor networks are essential for monitoring, control, and surveillance operations, but the limited battery capacity of wireless rechargeable sensor nodes (WRSNs) poses a significant challenge. To address this, on-demand charging from an external power source is fundamental for the effective operation of energy-critical WRSNs. In this article, the wireless charging of the independent WRSNs in a network is modeled as a service in a common competitive market, where multiple charging service providers (CSPs) indulge in a pricing war to maximize their profits by achieving fair market share based on area division. A competitive market scenario is considered where multiple non-cooperative CSPs are strategically located at their fixed grounded stations, and the most economical CSP gets requested from a WRSN for charging. The CSPs are associated with UAV-enabled chargers (UAVEC), which are dispatched to the concerned WRSNs with known positions and recharged wirelessly in a time-bound manner. This paper study a suitable pricing strategy for on-demand charging of the WRSNs in a competitive market scenario; and investigate the existence of Nash equilibrium (NE) for prices and profits of CSPs using a game-theoretic approach. The closed-form expressions of NE conditions and the CSP selection criterion for WRSNs are obtained, and the results are verified through simulations.\",\"PeriodicalId\":13052,\"journal\":{\"name\":\"IEEE Transactions on Green Communications and Networking\",\"volume\":\"9 2\",\"pages\":\"459-470\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Green Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10612772/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Green Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10612772/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
A Non-Cooperative Pricing Strategy for UAV-Enabled Charging of Wireless Sensor Network
Wireless sensor networks are essential for monitoring, control, and surveillance operations, but the limited battery capacity of wireless rechargeable sensor nodes (WRSNs) poses a significant challenge. To address this, on-demand charging from an external power source is fundamental for the effective operation of energy-critical WRSNs. In this article, the wireless charging of the independent WRSNs in a network is modeled as a service in a common competitive market, where multiple charging service providers (CSPs) indulge in a pricing war to maximize their profits by achieving fair market share based on area division. A competitive market scenario is considered where multiple non-cooperative CSPs are strategically located at their fixed grounded stations, and the most economical CSP gets requested from a WRSN for charging. The CSPs are associated with UAV-enabled chargers (UAVEC), which are dispatched to the concerned WRSNs with known positions and recharged wirelessly in a time-bound manner. This paper study a suitable pricing strategy for on-demand charging of the WRSNs in a competitive market scenario; and investigate the existence of Nash equilibrium (NE) for prices and profits of CSPs using a game-theoretic approach. The closed-form expressions of NE conditions and the CSP selection criterion for WRSNs are obtained, and the results are verified through simulations.