A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint
The selfishness and randomness of users in the mobile crowd sensing network could cause them unwilling to participate in sensing activities and lead to lower completion rates of sensing tasks. In order to deal with these problems, this paper proposes a novel incentive mechanism based on a new auctio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8664672/ |
| _version_ | 1819170134226370560 |
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| author | Yuanni Liu Xiaodan Xu Jianli Pan Jianhui Zhang Guofeng Zhao |
| author_facet | Yuanni Liu Xiaodan Xu Jianli Pan Jianhui Zhang Guofeng Zhao |
| author_sort | Yuanni Liu |
| collection | DOAJ |
| description | The selfishness and randomness of users in the mobile crowd sensing network could cause them unwilling to participate in sensing activities and lead to lower completion rates of sensing tasks. In order to deal with these problems, this paper proposes a novel incentive mechanism based on a new auction model for mobile crowd sensing, which consists of two consecutive stages. In the first stage, a novel Incentive Method based on Reverse Auction for Location-aware sensing (IMRAL) is proposed to maximize user utility. By introducing a task-centric method to determine the winning bids, it can provide higher user utility and higher task coverage ratio. To ensure the truthfulness of IMRAL, we design a unique payment determination algorithm based on critical payment for the incentive platform. In the second stage, we propose a user-interaction incentive model (UIBIM) to cover the situation that a user may drop out of the sensing activity. This new incentive model includes a dynamic double auction framework prompting users' interaction and a user matching algorithm based on a bipartite graph. The proposed new mechanism achieves the goal of improving task completion rates without increasing the cost of the incentive platform. The simulation results show that comparing with other solutions, such as a truthful auction for location-aware collaborative sensing in mobile crowdsourcing and incentive mechanism for crowdsourcing in the single-requester single-bid-model, IMRAL can achieve better performance in terms of average user utility and tasks coverage ratio, and the UIBIM can significantly improve task completion rates. |
| first_indexed | 2024-12-22T19:30:34Z |
| format | Article |
| id | doaj.art-7cfc4b6192bb48f092f241cb627f52b9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:30:34Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7cfc4b6192bb48f092f241cb627f52b92022-12-21T18:15:07ZengIEEEIEEE Access2169-35362019-01-017439334394710.1109/ACCESS.2019.29028828664672A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget ConstraintYuanni Liu0https://orcid.org/0000-0002-9305-3405Xiaodan Xu1Jianli Pan2Jianhui Zhang3Guofeng Zhao4School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaDepartment of Mathematics and Computer Science, University of Missouri–St. Louis, St. Louis, MO, USADigital Switching System Engineering and Technological R&D Center, Zhengzhou, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaThe selfishness and randomness of users in the mobile crowd sensing network could cause them unwilling to participate in sensing activities and lead to lower completion rates of sensing tasks. In order to deal with these problems, this paper proposes a novel incentive mechanism based on a new auction model for mobile crowd sensing, which consists of two consecutive stages. In the first stage, a novel Incentive Method based on Reverse Auction for Location-aware sensing (IMRAL) is proposed to maximize user utility. By introducing a task-centric method to determine the winning bids, it can provide higher user utility and higher task coverage ratio. To ensure the truthfulness of IMRAL, we design a unique payment determination algorithm based on critical payment for the incentive platform. In the second stage, we propose a user-interaction incentive model (UIBIM) to cover the situation that a user may drop out of the sensing activity. This new incentive model includes a dynamic double auction framework prompting users' interaction and a user matching algorithm based on a bipartite graph. The proposed new mechanism achieves the goal of improving task completion rates without increasing the cost of the incentive platform. The simulation results show that comparing with other solutions, such as a truthful auction for location-aware collaborative sensing in mobile crowdsourcing and incentive mechanism for crowdsourcing in the single-requester single-bid-model, IMRAL can achieve better performance in terms of average user utility and tasks coverage ratio, and the UIBIM can significantly improve task completion rates.https://ieeexplore.ieee.org/document/8664672/Mobile crowd sensingincentive mechanismtask coveragedouble auction |
| spellingShingle | Yuanni Liu Xiaodan Xu Jianli Pan Jianhui Zhang Guofeng Zhao A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint IEEE Access Mobile crowd sensing incentive mechanism task coverage double auction |
| title | A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint |
| title_full | A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint |
| title_fullStr | A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint |
| title_full_unstemmed | A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint |
| title_short | A Truthful Auction Mechanism for Mobile Crowd Sensing With Budget Constraint |
| title_sort | truthful auction mechanism for mobile crowd sensing with budget constraint |
| topic | Mobile crowd sensing incentive mechanism task coverage double auction |
| url | https://ieeexplore.ieee.org/document/8664672/ |
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