1 research outputs found
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 the task of
tile prediction or on the tasks of computing and communications, overlooking
the facts that these successively executed tasks have to share the same
duration to avoid the latency and the quality of experience (QoE) of proactive
VR streaming depends on the worst performance of the three tasks. In this
paper, we jointly optimize the duration of the observation window for
predicting tiles and the durations for computing and transmitting the predicted
tiles to maximize the QoE given arbitrary predictor and configured resources.
We obtain the global optimal solution with closed-form expression by
decomposing the formulated problem equivalently into two subproblems. With the
optimized durations, we find a resource-limited region where the QoE can be
improved effectively by configuring more resources, and a prediction-limited
region where the QoE can be improved with a better predictor. Simulation
results using three existing tile predictors with a real dataset demonstrate
the gain of the joint optimization over the non-optimized counterparts.Comment: 32 pages, one column, 7 figures, submitted to IEEE for possible
publicatio