An Incentive Mechanism Based on Lottery for Data Quality in Mobile Crowdsensing

Xinyu Hu, Shengjie Sun (), Zhi Lv and Jiaqi Liu
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Xinyu Hu: Tiangong Innovation School, Tiangong University, Tianjin 300387, China
Shengjie Sun: School of Computer Science and Engineering, Central South University, Changsha 410075, China
Zhi Lv: School of Computer Science and Engineering, Central South University, Changsha 410075, China
Jiaqi Liu: School of Computer Science and Engineering, Central South University, Changsha 410075, China

Mathematics, 2025, vol. 13, issue 10, 1-21

Abstract: Mobile Crowdsensing (MCS) leverages smart devices within sensing networks to gather data. Given that data collection demands specific resources, such as device power and network bandwidth, many users are reluctant to participate in MCS. Therefore, it is essential to design an effective incentive mechanism to encourage user participation and ensure the provision of high-quality data. Currently, most incentive mechanisms compensate users through monetary rewards, which often leads to users requiring higher prices to maintain their own profits. This, in turn, results in a limited number of users being selected due to platform budget constraints. To address this issue, we propose a lottery-based incentive mechanism. This mechanism analyzes the users’ bids to design a winning probability and budget allocation model, incentivizing users to lower their pricing and enhance data quality. Within a specific budget, the platform can engage more users in tasks and obtain higher-quality data. Compared to the ABSEE mechanism and the BBOM mechanism, the lottery incentive mechanism demonstrates improvements of approximately 47–74% in user participation and 14–66% in platform profits.

Keywords: crowdsensing; incentive mechanism; data quality; lottery (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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