Efficient transmission schemes are presented for streaming scalable video over a link with limited capacity. The objective is to select a transmission sequence of data units and their transmission schedule such that the overall video quality is maximized. For video with a single spatial layer, optimal transmission schemes are obtained for two general classes of hierarchical prediction structures, which include 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. Then, using the concept of virtual deadlines, an efficient sub-optimal scheme for the transmission of video with multiple spatial layers is proposed. Simulation results show that the proposed schemes substantially outperform two existing alternatives.

Efficient transmission schemes are presented for streaming scalable video over a link with limited capacity. The objective is to select a transmission sequence of data units and their transmission schedule such that the overall video quality is maximized. For video with a single spatial layer, optimal transmission schemes are obtained for two general classes of hierarchical prediction structures, which include 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. Then, using the concept of virtual deadlines, an efficient sub-optimal scheme for the transmission of video with multiple spatial layers is proposed. Simulation results show that the proposed schemes substantially outperform two existing alternatives.