UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory
In wireless sensor networks, terminal devices with restricted cost and size have limited battery life. Meanwhile, these energy-constrained devices are not easy to access, especially when the terminal devices are located in severe environments. To recharge the energy-constrained devices and extend th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/15/11/2065 |
| _version_ | 1797457636264771584 |
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| author | Chunxia Su Jichong Guo Zhenping Chen Jingwei Fu Guizhang Chen |
| author_facet | Chunxia Su Jichong Guo Zhenping Chen Jingwei Fu Guizhang Chen |
| author_sort | Chunxia Su |
| collection | DOAJ |
| description | In wireless sensor networks, terminal devices with restricted cost and size have limited battery life. Meanwhile, these energy-constrained devices are not easy to access, especially when the terminal devices are located in severe environments. To recharge the energy-constrained devices and extend their network service time, unmanned aerial vehicles (UAVs) equipped with wireless power chargers are leased by the third-party control center. To incent the participation of UAVs with different charging capabilities and ensure the strategy-proofness of the incentive mechanism, a hidden information based contract theory model, specifically adverse selection, is introduced. By leveraging individual rationality and incentive compatibility, a contract theory based optimization problem is then formulated. After reducing redundant constraints, the optimal contract items are derived by Lagrangian multiplier. Finally, numerical simulation results are implemented to compare the prepared algorithm with three other baselines, which validates the effectiveness of our proposed incentive mechanism. |
| first_indexed | 2024-03-09T16:24:52Z |
| format | Article |
| id | doaj.art-b26d803c47ab401b9a78075ecddd6c15 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T16:24:52Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-b26d803c47ab401b9a78075ecddd6c152023-11-24T15:08:57ZengMDPI AGSymmetry2073-89942023-11-011511206510.3390/sym15112065UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract TheoryChunxia Su0Jichong Guo 1Zhenping Chen2Jingwei Fu3Guizhang Chen4School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaSchool of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaSchool of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaSchool of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaSchool of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, ChinaIn wireless sensor networks, terminal devices with restricted cost and size have limited battery life. Meanwhile, these energy-constrained devices are not easy to access, especially when the terminal devices are located in severe environments. To recharge the energy-constrained devices and extend their network service time, unmanned aerial vehicles (UAVs) equipped with wireless power chargers are leased by the third-party control center. To incent the participation of UAVs with different charging capabilities and ensure the strategy-proofness of the incentive mechanism, a hidden information based contract theory model, specifically adverse selection, is introduced. By leveraging individual rationality and incentive compatibility, a contract theory based optimization problem is then formulated. After reducing redundant constraints, the optimal contract items are derived by Lagrangian multiplier. Finally, numerical simulation results are implemented to compare the prepared algorithm with three other baselines, which validates the effectiveness of our proposed incentive mechanism.https://www.mdpi.com/2073-8994/15/11/2065unmanned aerial vehicleswireless chargingenergy tradingincentive mechanismcontract theory |
| spellingShingle | Chunxia Su Jichong Guo Zhenping Chen Jingwei Fu Guizhang Chen UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory Symmetry unmanned aerial vehicles wireless charging energy trading incentive mechanism contract theory |
| title | UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory |
| title_full | UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory |
| title_fullStr | UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory |
| title_full_unstemmed | UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory |
| title_short | UAV-Assisted Wireless Charging Incentive Mechanism Design Based on Contract Theory |
| title_sort | uav assisted wireless charging incentive mechanism design based on contract theory |
| topic | unmanned aerial vehicles wireless charging energy trading incentive mechanism contract theory |
| url | https://www.mdpi.com/2073-8994/15/11/2065 |
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