A Truthful Location-Protected Mobile Crowdsensing Framework with User Mobility

Mobile Crowdsensing (MCS) is a promising paradigm for the large-scale sensing. In this paper, we aim to build a truthful framework of MCS taking user mobility and incentive into account. The proposed framework is composed of two challenging problems, path planning and incentive mechanism design. In path planning, every user as a worker independently plans a tour to carry out tasks based on its own strategy. In incentive mechanism design, the platform leverages a mechanism to select the winners and determine the payments. To solve these two problems, a heuristic bidirectional searching algorithm is proposed for path planning and an incentive mechanism is designed. The proposed mechanism is proved to be computationally efficient, individually rational, and truthful. Finally, the simulation results show that our proposed heuristic algorithm outperforms the baseline algorithms and approaches the optimal solution in path planning. Our proposed mechanism has a total payment smaller than that of a Vickrey-Clarke-Groves (VCG) mechanism.