A dynamic social content caching under user mobility pattern

Online content propagation gives rise to tremendous data explosion and requires efficient management for a large amount of network resources, after next generation network service predomination. Especially in the age of social network, the way of content propagation and consumption has significantly changed from requesting to sharing. Since massive users are tending to influenced by the trends in social community and mainstream media, content caching becomes an effective method for providing better quality of service for such social relationships. A key challenge is traditional caching strategies cannot meet the dynamic variation in geo-social environments. In this paper, we propose a dynamic social content caching scheme with social user mobility. We employ a combination of cooperative filtering recommendation and cache update algorithm to effectively predict and manage cache updates. Simulation results show that our caching method over performs than classical caching methods that rely on the historical popularity prediction.