Exploring Mobility Behaviours of Moving Agents from Trajectory traces in Cloud-Fog-Edge Collaborative Framework

Both analyzing mobility traces and understanding a user's movement semantics from mobile sensor data are challenging issues in ubiquitous computing systems. With the pervasiveness of sensor technologies, wireless networks and GPS-equipped devices, a huge volume of location information is being accumulated. Several techniques have been proposed to analyze the mobility traces and extract informative knowledge for varied location-aware applications. However, all of these applications necessitate an effective mobility-analysis framework to capture the movement behavior of individuals in minimum delay. This paper aims to develop a cloud-based mobility analytics framework to model peoples' mobility behaviour in varied granular scale and extract usable knowledge to provision location-aware services. The preliminary experimental results on real-life dataset depict the effectiveness of our proposed framework.