Social-Aware Incentive Mechanism for Participatory Sensing

Abstract

As an efficient way to collect sensing data, participatory sensing has been receiving more and more attentions and its applications cover various areas such as traffic control and management, environmental monitoring, etc. In a participatory sensing system, Service Provider (SP) works as the task promulgator, Smartphone User (SU) works as the task executor and the Platform handles the sensing task allocation procedure. Incentive mechanism plays a key role in stimulating both SPs and SUs to take part in the participatory sensing system. Most of previous works on the incentive mechanism design do not consider the social relationship of SUs, which may degrade the performance of the participatory sensing system. In this paper, we take the social relationship of SUs into consideration, and design a Social-Aware Incentive Mechanism (SAIM) which can achieve high system performance and satisfy the properties of individual rationality, budget balance, the completely truthful for SPs, and partially truthful for SUs. Simulation results show the better performance of the proposed incentive mechanism compared with two other counterparts in terms of social utility and social effect. Specifically, the proposed mechanism can improve the social utility by 12% and 16% compared with McAfee and random selection, respectively, with the number of smartphone users m = 100.