Prediction, Communication, and Computing Duration Optimization for VR Video Streaming

Proactive tile-based video streaming can avoid motion-to-photon latency of wireless virtual reality (VR) by computing and delivering the predicted tiles to be requested before playback. All existing works either focus on designing predictors or allocating communications resources. Yet latency, successively executed prediction, communication, tasks should accomplished within a predetermined time. Moreover, quality experience (QoE) proactive VR depends worst performance three tasks. In this paper, we jointly optimize duration observation window for predicting durations transmitting tiles, aimed at balancing maximize QoE given arbitrary predictor configured We obtain closed-form optimal solution decomposing formulated problem equivalently into two subproblems. With optimized durations, find resource-limited region where increases rapidly with resources, prediction-limited improved more efficiently better predictor. Simulation results using real dataset validate analysis demonstrate gain from joint optimization over non-optimized counterparts.