Quality of Sensing Aware Budget Feasible Mechanism for Mobile Crowdsensing

Abstract

In a mobile crowdsensing system, the platform utilizes ubiquitous smartphones to perform sensing tasks. For a successful mobile crowdsensing application, the consideration of the heterogeneity of quality of sensing from different users as well as a proper incentive mechanism to motivate users to contribute to the system are essential. In this paper, we introduce the quality of sensing into incentive mechanism design. Under a budget constraint, the platform aims to maximize the valuation of the performed tasks, which depends on the quality of sensing of the users. We propose ABSee, an auction-based budget feasible mechanism, which consists of a winner selection rule and a payment determination rule. ABSee is designed by adopting a greedy approach. We obtain the approximation ratio of ABSee, which significantly improves the approximation ratio of the existing budget feasible mechanisms in many cases. We further show that the approximation ratio approaches $\frac {2e}{e-1}$ when a large number of smartphone users participate in the system. ABSee also satisfies the properties of computational efficiency, truthfulness, individual rationality, and budget feasibility. Extensive simulation results show that ABSee provides a higher valuation to the platform when compared with existing budget feasible mechanisms in the literature.