1 Sangeun Han, Athina Markopoulou Transmitting Scalable Video over a DiffServ network EE368C Project Proposal Sangeun Han, Athina Markopoulou 1/30/01

2 Sangeun Han, Athina Markopoulou References - Motivation Scalable Video Coding & Transmission –U.Horn & B. Girod, “Scalable video transmission for the Internet”, Computer Networks and ISDN Systems, –M. van der Schaar & H.Radha, “A hybrid temporal-SNR FGS for the Internet video”, IEEE Trans. on Circuits and Systems for Video Technology. –J.Kimura & F.Tobagi, “Perceived quality and bandwidth characterization of layered MPEG-2 video encoding”, SPIE –S.McCanne, N.Vetterli & V.Jacobson, “Low complexity video coding for receiver -driven layered multicast”, JSAC Differentiated Services – – RFC 2475, RFC 2597 Software –NS simulator: –ITU-T Recommendation H.263 (Annex O)

3 Sangeun Han, Athina Markopoulou Overview 1.Scalable video coding: –MPEG-2, H.263: SNR, Spatial, Temporal, –MPEG-4, H.26L: FGS 2.Transmission over the network: – In general – DiffServ 3. Our scenario –Simulation setup –Issues

4 Sangeun Han, Athina Markopoulou Scalable Video Coding

5 Sangeun Han, Athina Markopoulou Fine-Granularity Scalability FGST Notes Problems: limited scalability, error propagation Standards: MPEG-4, H.26L FGS advantages: transmission over networks w/ BW variation, error resilience BW variation

6 Sangeun Han, Athina Markopoulou Transmission Loss Need to use the available bandwidth to send the most important data Small loss translates into drastic quality degradation (loss of important data + temporal dependence) Transmission over the Internet is lossy Server Receiver Network

7 Sangeun Han, Athina Markopoulou Solutions 1.Feedback + adapt transmission rate to variations –Disadvantages: complexity, granularity of BW adjustments, delay in feedback, overhead, inappropriate for multicast or high variability 2.Receiver Driven Layered Multicast –Problems: overhead, delay, granularity of BW 3.Smoothing + Admission control –Idea: limit stream and load variability. –Disadvantages: complexity, overhead, delay, model 4.Loss happens – control its effect by dealing with it intelligently: –Unequal error protection –Priority dropping Use the available bandwidth for the most important data

8 Sangeun Han, Athina Markopoulou Priority Dropping Loss is inevitable. Limit its effect when it happens. Prioritize information according to importance (contribution to quality) Drop packets according to their priority Low drop Drop prob High drop Buffer occupancy 1 0 Importa nt Less Important Advantages: simple sender, handles heterogeneous receivers + short term congestion

9 Sangeun Han, Athina Markopoulou QoS architectures for the Internet Best Effort Integrated Services Differentiate d Services 1.Best effort: no guarantees 2.Integrated Services (IntServ): Per-flow guarantees 3.Differentiated Services (DiffServ): Per aggregate guarantees

10 Sangeun Han, Athina Markopoulou Example of a DiffServ node Packet are marked (DSCP) conditioning classification AF 11 Each packet is treated according to this marking

11 Sangeun Han, Athina Markopoulou AF class IETF DiffServ WG in RFC 2597 defines 4 “Assured Forwarding” (AF) classes Each AFx class: marking with AFx1, AFx2, AFx3 –Minimum BW guaranteed for the AFx aggregate. –3 dropping priorities (1,2,3). AFx1 Drop prob AFx3 Buffer occupancy 1 0 AFx2 AFx1 AFx2 AFx3

12 Sangeun Han, Athina Markopoulou Scalable video in DiffServ Use a particular AF Class for Video Mark different layers with different AF dropping priorities Define mechanisms to be used for the Video AF Class Give rationale on how to create layers to work together with AF

13 Sangeun Han, Athina Markopoulou Approach Layered video H.263+ Encoder + Layering RTP Packet. Decoding + [Error Conceal.] Depackt. (Packet Loss) RTP Transport Playback buffer Marker DiffServ Network Simulation & trying scenarios

14 Sangeun Han, Athina Markopoulou Issues Purpose: show benefit of combining layering and priority dropping Network point of view: Provide recommendations for DiffServ standardization: –How many priorities are really needed? –How to configure AF class? –How to choose the layering parameters? Coding point of view: Explore benefit of layering/FGS: –under Internet loss scenarios E.g., Tradeoff between motion smoothness and quality of pictures under buffer loss, or mix with bursty data –Significance of fine granularity for real scenarios

15 Sangeun Han, Athina Markopoulou Suggestions..?