Reputation-aware incentive mechanism for participatory sensing

Participatory sensing can leverage a large amount of smartphone users to collect and analysis sensing data. Conducting sensing task consumes the resource of smartphone user. Therefore, in order to motivate selfish and rational smartphone users to participate in sensing task, incentive mechanism plays a key role in the success of this new sensing paradigm by providing appropriate compensation (e.g., payment or reward) to smartphone users. Most of previous works on the incentive mechanism design focus on the participation of mobile users, rather than the quality of sensing data. In this paper, we take the quality of sensing data into consideration, and design a reputation-aware incentive mechanism which can maximize the weighted social welfare of the whole system, guarantee the truthfulness and individual rationality. Simulation results show the better performance of the proposed incentive mechanism compared with three other counterparts in terms of weighted social welfare and average reputation. Specifically, the proposed mechanism can improve the weighted social welfare by 8.65% and 48.16% compared with TSCM and random selection, respectively, with the number of smartphone users N = 18.