基于移动社交网络的群智感知社群化任务分发

A "platform-community-user" socialization task allocation approach was proposed by leveraging participant users' group social characteristics in view of the shortcomings of traditional "platform-user" mobile crowd sensing model. Firstly, a dynamic community division clustering was achieved based on the similarity of users' spatiotemporal mobility distribution. And then, via the roles of the community organizer and subordinate, a novel mobile crowd sensing task mechanism, i.e., primary community distribution and secondary user selection, was proposed by incorporating social intimacy connection network. The experimental results on public WTD data set show that, compared with the traditional task allocation method, the proposed method can effectively improve the task completion rate, enhance the robustness of the execution process, reduce the number of execution iteration and the communication overhead.