Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network
Mobile crowdsensing (MCS) has become a popular and promising paradigm in various sensing applications in urban scenarios. In recent years, some social network-based MCS systems, which utilizing the social relationship to recruit participants or perform sensing tasks, have been proposed. However, non...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8452970/ |
| _version_ | 1818643028954316800 |
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| author | Lingyun Jiang Xiaofu Niu Jia Xu Yuchan Wang Yongqi Wu Lijie Xu |
| author_facet | Lingyun Jiang Xiaofu Niu Jia Xu Yuchan Wang Yongqi Wu Lijie Xu |
| author_sort | Lingyun Jiang |
| collection | DOAJ |
| description | Mobile crowdsensing (MCS) has become a popular and promising paradigm in various sensing applications in urban scenarios. In recent years, some social network-based MCS systems, which utilizing the social relationship to recruit participants or perform sensing tasks, have been proposed. However, none of them have taken into consideration both the time-sensitive and Sybil-proofness, which are the two key problems for the MCS systems in the social network context. We present two social network-based MCS system models, and formulize the Sybil attack models for each model. We design two incentive mechanisms based on reverse auction, time-sensitive and sybilproof incentive mechanism in multi-bid model (TSSP-M), and time-sensitive and sybil-proof incentive mechanism in single-bid model (TSSP-S), for each of two system models. Through both rigorous theoretical analyses and extensive simulations, we demonstrate that TSSP-M satisfies the desirable properties of computational efficiency, individual rationality, truthfulness, time-sensitive, Sybil-proofness, and optimization; TSSP-S achieves individual rationality, truthfulness, time-sensitive, and Sybil-proofness. |
| first_indexed | 2024-12-16T23:52:27Z |
| format | Article |
| id | doaj.art-730df8ef208d4e7f92103888055210e2 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T23:52:27Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-730df8ef208d4e7f92103888055210e22022-12-21T22:11:17ZengIEEEIEEE Access2169-35362018-01-016481564816810.1109/ACCESS.2018.28681808452970Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social NetworkLingyun Jiang0Xiaofu Niu1Jia Xu2https://orcid.org/0000-0002-0523-9673Yuchan Wang3Yongqi Wu4Lijie Xu5Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaJiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaJiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaJiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaJiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaJiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, ChinaMobile crowdsensing (MCS) has become a popular and promising paradigm in various sensing applications in urban scenarios. In recent years, some social network-based MCS systems, which utilizing the social relationship to recruit participants or perform sensing tasks, have been proposed. However, none of them have taken into consideration both the time-sensitive and Sybil-proofness, which are the two key problems for the MCS systems in the social network context. We present two social network-based MCS system models, and formulize the Sybil attack models for each model. We design two incentive mechanisms based on reverse auction, time-sensitive and sybilproof incentive mechanism in multi-bid model (TSSP-M), and time-sensitive and sybil-proof incentive mechanism in single-bid model (TSSP-S), for each of two system models. Through both rigorous theoretical analyses and extensive simulations, we demonstrate that TSSP-M satisfies the desirable properties of computational efficiency, individual rationality, truthfulness, time-sensitive, Sybil-proofness, and optimization; TSSP-S achieves individual rationality, truthfulness, time-sensitive, and Sybil-proofness.https://ieeexplore.ieee.org/document/8452970/Mobile crowdsensingincentive mechanism designtime-sensitivesybil-proofsocial network |
| spellingShingle | Lingyun Jiang Xiaofu Niu Jia Xu Yuchan Wang Yongqi Wu Lijie Xu Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network IEEE Access Mobile crowdsensing incentive mechanism design time-sensitive sybil-proof social network |
| title | Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network |
| title_full | Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network |
| title_fullStr | Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network |
| title_full_unstemmed | Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network |
| title_short | Time-Sensitive and Sybil-Proof Incentive Mechanisms for Mobile Crowdsensing via Social Network |
| title_sort | time sensitive and sybil proof incentive mechanisms for mobile crowdsensing via social network |
| topic | Mobile crowdsensing incentive mechanism design time-sensitive sybil-proof social network |
| url | https://ieeexplore.ieee.org/document/8452970/ |
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