Adaptive video streaming with long term feedbacks

This paper proposes a video streaming system optimizing resource utilization when the media server only disposes of long term feedbacks from the client. Based on a partial knowledge of the network, we developed a scheduling algorithm that exploits the scalable video coding (SVC) properties to estimate packets importance and that takes into account packet delay dependencies to better anticipate congestion situations. Compared to more conventional streaming systems, experimental results show that our approach allows to better face network condition degradation like bandwidth reduction or packet error rate increase.