Deadline Sensitive Task Assignment in Mobile Crowd Sensing: A greedy Approach

In mobile crowd-sensing, the diversity of worker and task locations and trajectories of worker makes the optimal task allocation problem more challenging. The different trajectory of worker leads to different response time and traveling cost. In this paper, we compute the trajectory of the worker by applying an asymmetric traveling salesman problem (ATSP) heuristic algorithm. Furthermore, We formulate Deadline Sensitive Task Assignment problem (DSTA) mathematically and propose a greedy strategy with the aim of maximizing the remaining budget while considering several constraints. The experiment shows the performance of our proposed method for different parameters.