Abstract: This paper studies the problem of worker recruitment algorithm for mobile crowd sensing system (MCS). Recruitment algorithms based on cloud platform cannot meet the needs of large scale network real-time tasks, a three-tier worker recruitment algorithm(ECRecruitment) based on edge cloud collaboration is proposed, which aims to reduce the data transmission delay and the energy consumption of intelligent devices. The cloud service layer is responsible for task reception, division, release and result collection; The edge layer is responsible for obtaining the real-time information of workers and constructing the recruitment model of workers; The perceptual layer is responsible for task propagation and data collection. ECRecruitment considers multiple influencing factors, such as sensor type, worker quotation, maximum number of assigned tasks, etc. The experimental results show that ECRecruitment can not only meet the cost and time constraints, but also achieve good performance in space coverage and operation time.

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