Abstract
Task allocation is a significant research issue in Mobile Crowd Sensing, and research on Mobile Crowd-Sensing has indicated that it can be applied in Vehicle Ad Hoc Networks. However, few of the works pay attention to the task allocation issues in Mobile Crowd-Sensing. In our paper, we propose a task allocation scheme in Mobile Crowd-Sensing. In order to make it applicable to Vehicle Ad Hoc Networks, we introduce the Markov location prediction in our scheme, which can perform a location prediction before the task allocation, and a differential privacy mechanism to protect the location privacy of vehicles. Besides, we design a calculation method of task completion rate that can ensure that the task has a significant probability of completing successfully and the number of notified servers is as small as possible. Experiments are also implemented to evaluate the performance of our scheme, which demonstrate that our proposed scheme is feasible and efficient.
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