Abstract: Since the recruitment algorithms based on cloud platform cannot meet the needs of large scale network real-time tasks, an edge-cloud collaboration recruitmentalgorithm is proposed whose aim is to reduce the data transmission delay and the energy consumption of intelligent devices. The cloud service layer performs task reception, division, release and result collection; the edge layer performs obtaining the real-time information of workers and constructing the recruitment model of workers,while the perceptual layer performs task propagation and data collection. The experimental results show that the proposed algorithm can not only meet the cost and time constraints, but also achieve good performance in space coverage and time by taking consideration of sensor type, worker quotation and the maximum number.

Key words: mobile crowd sensing, worker recruitment, edge-cloud collaboration, spatial coverage