The application is a crowd-sensing task
allocation method based on proficiency cooperation. Firstly, the crowd-sensing scene is divided into multiple areas, and the users in each area are divided into a group, and one group leader is selected in each group. Secondly, the sensing platform sends a task set to the users. The users sort the tasks from early to late according to the deadlines, and obtain a task
queue. When the users receive a new task, the new task is inserted into the task
queue according to the deadline of the new task. Then, when the task quantity of the users does not increase suddenly, the users execute the tasks according to the order of the task
queue. When the task quantity increases suddenly, the users send the task queue to the group leader. If the task quantity of the group leader increases suddenly, the group leader feeds back to the sensing platform and requests the nearby
user group for assistance. The sudden increase of the task quantity refers to that the ratio of the to-be-completed task quantity of the user to the
processing speed is greater than a set threshold. Finally, the group leader obtains the
global optimal solution of the target function on the device of the group leader by using a
swarm intelligence algorithm, and allocates the tasks in the task queue according to the
global optimal solution. The method considers the balance of the task quantity and the balance of the
processing speed of each user while striving to minimize the overall
task completion time, thereby effectively reducing the
operating cost.