Poster: TRIM: A Truthful Incentive Mechanism for Dynamic and Heterogeneous Tasks in Mobile Crowdsensing

Abstract

Stimulating user participation is of paramount importance for mobile crowdsensing applications to obtain high-quality data. Although many incentive mechanisms have been designed, most of them ignore the dynamic arrivals and different sensing requirements of tasks. Thus, the existing mechanisms will fail when being applied to the realistic scenario where tasks are publicized dynamically and heterogeneous with different sensing requirements of locations, time durations and sensing times. In this work, we propose an auction-based truthful mechanism for realistic mobile crowdsensing. Through extensive simulations, we demonstrate that our mechanism can satisfy the desired properties of truthfulness, individual rationality, computational efficiency with both low social cost and low total payment.