In this study, we characterize user sessions of the popular multimedia Web 2.0 site, YouTube. We observe YouTube user sessions by making measurements from an edge network perspective. Several characteristics of user sessions are considered, including session duration, inter-transaction times, and the types of content transferred by user sessions. We compare and contrast our results with "traditional" Web user sessions. We find that YouTube users transfer more data and have longer think times than traditional Web workloads. These differences have implications for network capacity planning and design of next generation synthetic Web workloads.
In REF , a study of user sessions of YouTube was conducted.
Characterizing user sessions on YouTube
Electronic Imaging
Engineering Computer Science