Optimal Frame Transmission for Scalable Video with Hierarchical Prediction Structure

TL;DR

This paper introduces an optimal transmission scheme for scalable video streaming that maximizes quality by selecting and scheduling frames based on hierarchical prediction structures, outperforming existing methods.

Contribution

It develops a jointly optimal frame selection and scheduling algorithm for hierarchical video structures with quadratic complexity, improving streaming quality.

Findings

Optimal scheme outperforms existing alternatives in simulations.

Structural properties enable efficient joint frame selection and scheduling.

Algorithm applicable to general hierarchical prediction structures.

Abstract

An optimal frame transmission scheme is presented for streaming scalable video over a link with limited capacity. The objective is to select a transmission sequence of frames and their transmission schedule such that the overall video quality is maximized. The problem is solved for two general classes of hierarchical prediction structures, which include as a special case the popular dyadic structure. Based on a new characterization of the interdependence among frames in terms of trees, structural properties of an optimal transmission schedule are derived. These properties lead to the development of a jointly optimal frame selection and scheduling algorithm, which has computational complexity that is quadratic in the number of frames. Simulation results show that the optimal scheme substantially outperforms three existing alternatives.