Towards user-aware Peer-to-Peer live video streaming systems

The involvement of end hosts to relay content to each other makes Peer-to-Peer (P2P) video streaming systems potentially scalable and easy to deploy with low cost. Since end hosts are controlled by users, their intermittent presence directly impacts the performance of these systems. Current approaches do not consider and integrate user behavior in their design, hence suffering from Quality-of-Service (QoS) issues. In this thesis, we focus on the user behavior from its understanding to modeling and integrating into P2P systems. We propose an autonomous management framework that (1) enables peers to learn the behavior of users and organize themselves in such a way to minimize its impact and improve the streaming quality, and (2) controls the topology of push-based systems through a stabilization process that continuously pushes unstable peers towards the leaves of the tree. We evaluate and compare these models through both simulations and experimentations over PlanetLab which show that the integration of user behavior into P2P systems considerably improves their performance.