A Fair Incentive Mechanism for Crowdsourcing in Crowd Sensing

Crowd sensing (CS) is a new paradigm of collecting large amounts of sensing information from a crowd. Unfortunately, not everyone is willing to participate in sensing tasks or provide high-quality information. Offering incentives is a common method of increasing the success of CS. Existing incentive mechanisms based on auction models lack deep consideration regarding the effects of malicious competition behavior and the “free-riding” phenomenon in crowdsourcing services. The design proposed in this paper focuses on an incentive mechanism based on a reverse auction. First, the crowdsourcing system incentive model is built. Second, an incentive mechanism is proposed based on an auction which combines the concepts of reverse auctions and Vickrey auctions. Next, proof that the mechanism is computationally efficient, individually rational, budget-balanced, truthful, and honest is provided. Simulation results indicate that the proposed incentive mechanism can effectively improve fairness of the bids and the quality of the sensed data.