A QoS-aware online incentive mechanism for mobile crowd sensing

Abstract

Mobile crowd sensing has emerged as a compelling paradigm to provide sensing data for web information system. A number of incentive mechanisms have been proposed to stimulate smartphone users participation. The vast majority of work fails to take QoS into consideration. In general, QoS is of paramount importance as a standard criterion for mobile crowd sensing applications. In this paper, we propose a QoS-aware online incentive mechanism for maximizing the social welfare. In consideration of the dynamics, we design an approximation algorithm with ½ -competitive ratio to solve the online allocation problem. We conduct rigorous theoretical analysis and extensive experimental simulations, demonstrating that the proposed mechanism achieves truthfulness, individual rationality, high computational efficiency and low overpayment ratio.