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  • 标题:Incentive mechanism based on Stackelberg game under reputation constraint for mobile crowdsensing
  • 本地全文:下载
  • 作者:Xiaoxiao Yang ; Jing Zhang ; Jun Peng
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2021
  • 卷号:17
  • 期号:6
  • 页码:1
  • DOI:10.1177/15501477211023010
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Encouraging a certain number of users to participate in a sensing task continuously for collecting high-quality sensing data under a certain budget is a new challenge in the mobile crowdsensing. The users’ historical reputation reflects their past performance in completing sensing tasks, and users with high historical reputation have outstanding performance in historical tasks. Therefore, this study proposes a reputation constraint incentive mechanism algorithm based on the Stackelberg game to solve the abovementioned problem. First, the user’s historical reputation is applied to select some trusted users for collecting high-quality sensing data. Then, the two-stage Stackelberg game is used to analyze the user’s resource contribution level in the sensing task and the optimal incentive mechanism of the server platform. The existence and uniqueness of Stackelberg equilibrium are verified by determining the user’s optimal response strategy. Finally, two conversion methods of the user’s total payoff are proposed to ensure flexible application of the user’s payoff in the mobile crowdsensing network. Simulation experiments show that the historical reputation of selected trusted users is higher than that of randomly selected users, and the server platform and users have good utility.
  • 关键词:Stackelberg game; mobile crowdsensing; historical reputation; optimal response strategy; incentive mechanism
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