Unified framework for optimal video streaming

We study the problem of how to stream layered video (live and stored) over a lossy packet network in order to optimize the video quality that is rendered at the receiver. We present a unified framework that combines scheduling, FEC error protection, and decoder error concealment. In the context of the unified framework, we study both the case of a channel with perfect state information and the case of a channel with imperfect state information (delayed or lost feedback). We adapt the theory of infinite?horizon, average?reward Markov decision processes (MDPs) with average?cost constraints to the problem. Based on simulations with MPEG-4 FGS video, we show that (1) optimizing together scheduling, FEC error correction and error concealment improves performance significantly and (2) policies with static error protection give near?optimal performance. We also find that degradations in quality for a channel with imperfect state information are small; thus our MDP approach is suitable for networks with long end?to?end delays.