A Reverse Auction Incentive Mechanism Based on the Participant’s Behavior in Crowdsensing

Crowdsensing has been integrated into many aspects of human life. Compared with the general mode of perception which need to arrange a large number of sensors in advance, crowdsensing uses the idea of crowdsourcing to distribute tasks to participants carrying mobile sensing devices with them, which can save the cost of deploying sensing nodes. Therefore, how to make people actively participate in perception has become a hot issue. The existing incentives mainly include bonus incentives, game entertainment incentives, and social relationship incentives. This paper proposes a reverse auction incentive mechanism based on the participant’s behavior. Specifically, we analyze the user’s behavior and build a model of participant competency assessment firstly; then, according to the above analysis, each user is scored and the reward is distributed using the improved reverse auction algorithm. The experimental results show the effect of the proposed method.