Task Distribution Based on User Attention and Time Supervision

In the mobile crowd sensing network, how to complete the sensing task assigned by the publisher within a limited time is an important problem faced by the mobile crowd sensing task distribution. To solve this problem, we propose a task distribution algorithm TDUATS based on user attention and time supervision in order to make the sensing users cooperate closely and feed back the sensing tasks to the sender in time. In the algorithm, the concepts of user attention, initial supervision, process supervision and completion supervision are proposed at first, and then the relationship between users who perform sensing tasks is analyzed. In order to monitor the process of task execution, the attention model among users is established, and the sensing tasks are distributed on this basis.Two real-world mobility datasets experiments demonstrate that the our proposed algorithm can not only complete the sensing task within a limited time, but also supervise the process of task execution, which is conductive to the publisher to timely understand the execution of the task, and plays a good role in improving the satisfaction of task execution. At the same time, compared with the comparison algorithms, sender and publisher can understand the task execution process in time, effectively improving the satisfaction of both parties.