Social-aware incentive mechanism for fullview covered video collection in crowdsensing

Abstract

Compared with a traditional fixed sensor network, mobile crowdsensing provides an efficient way to collect sensing data. However, conducting sensing tasks consumes the resources of mobile users (e.g. battery, storage memory, time). Therefore, incentive mechanism design plays a key role in efficiently collecting the sensing data in a mobile crowdsensing system. Most of existing works about the incentive mechanism design simply use a constant to describe the data quality. In this study, the authors focus on the collection of video clips and introduce multiple parameters to evaluate the quality of the collected data. By jointly considering the social relationship of mobile users, they propose a social-aware incentive mechanism to achieve the full-view coverage for a target by efficiently collecting video clips. The proposed mechanism satisfies the properties of individual rationality, truthful and computational efficiency. Simulation results show better performance of the proposed mechanism compared with random selection and aspect based selection. In specific, with the number of users n = 80, the proposed mechanism can improve the data collector's utility by 485% and 33% compared with random selection and aspect based selection, respectively.