A Task Allocation Algorithm for Coal Mine Mobile Crowd Sensing Based on Weighted Undirected Graph

Existing applications of mining intelligent mobile terminals are all for the sensing of individual terminals, without considering the group attributes of terminal carriers and the cooperation opportunities brought by terminal movement, which is unable to complete large-scale and complex sensing tasks. In this article, mobile crowd sensing and mine safety monitoring are combined to construct the mobile crowd sensing network for coal mine. Aiming at the task allocation problem, a task allocation mechanism based on a weighted undirected graph is proposed. First, considering the similarity of task completion location and time and quality of data collected, the reputation evaluation model of miners is designed. In order to optimize the reputation of miners participating in the task, an emergency task allocation algorithm based on the weighted undirected graph is proposed. Second, based on the fatigue degree of miners and the residual energy of intelligent mobile terminals, the miner status evaluation model is constructed, which is combined with the reputation model to design a nonemergency task allocation algorithm, aiming at further optimizing the task allocation results. The simulation results show that the proposed algorithm has better performance in allocation time for sensing task, task allocation success rate, average reputation, and status value of miners.