A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds

While demands on video traffic above mobile webs have been souring, the wireless link capacity cannot retain up alongside the traffic demand. The gap amid the traffic demand and the link capacity, alongside alongside time-varying link conditions, aftermath in poor ability quality of video streaming above mobile webs such as long buffering period and intermittent disruptions. Leveraging the cloud computing knowledge, we counsel a new mobile video streaming framework, dubbed AMES-Cloud, that has two main parts: AMoV (adaptive mobile video streaming) and ESoV (efficient communal video sharing). AMoV and ESoV craft a confidential agent to furnish video streaming services effectually for every single mobile user. For a given user, AMoV lets her confidential agent adaptively adjust her streaming flow alongside a scalable video coding method established on the feedback of link quality. Likewise, ESoV monitors the communal web contact amid mobile users, and their confidential agents endeavor to prefetch video content in advance. We apply a prototype of the AMES-Cloud framework to clarify its performance. It is shown that the private