Proposed by R. Puri, K.W. Lee, K. Ramchandran and V. Bharghavan

1. An Integrated Source Transcoding and Congestion Control Paradigm for Video Streaming in the Internet Proposed by R. Puri, K.W. Lee, K. Ramchandran and V. Bharghavan Presented by Felix

2. Agenda • Introduction • LIMD/H Congestion Control • MD-FEC Transcoder • Performance Summary • Discussion

3. Introduction • More and more video traffic are using best-effort and unreliable channel service (eg. UDP) because of its low delay feature • Explicit TCP-friendly Congestion Control policy is required to achieve fairness with other TCP flows

4. Introduction • Two questions: • How to control the transmission rate? • How to control the video source to adapt to the transmission rate?

5. LIMD/H Congestion Control • LIMD (Linear Increase Multiplicative Decrease) • r : sending rate • f : fraction of packet loss in the last period • If f = 0, r  r + a • If f > 0, r  r * (1-b) • Typically, (a, b) = (1, 0.5)

6. LIMD/H Congestion Control • Problems of traditional LIMD • React identically and aggressively to any kind of packet loss, both congestion induced and non-congestion induced. • Even if the channel bandwidth is invariant, the sending rate fluctuates greatly

7. LIMD/H Congestion Control • LIMD/H (LIMD with History) • h : a history factor • If f = 0, r  r + a, and h  1 • If f > 0, r  r *(1 – b’*h), and h  2h • b’ should be small to reduce the variation of sending rate

8. LIMD/H Congestion Control

9. MD-FEC Transcoder • Layered or Multi-Resolution (MR) source coding is a common coding method to provide quality/bit-rate scalability Raw Video Stream Base Layer Multiresolution (MR) Source Coder Enhancement Layer 1 Enhancement Layer 2 . . Enhancement Layer N

10. MD-FEC Transcoder • Problem of MR coding • Different quality layers have different importance  Prioritized Eg. The client receiving packets of layers [0, 1, 2, 4] will only get quality as just receiving [0, 1, 2] • However, the network treats every packet, no matter which layer it belongs to, identically  Non-prioritized • Loss of lower layers’ packets makes some other successfully transmitted higher layers’ packets useless. • Low robustness in a lossy channel

11. MD-FEC Transcoder • MD-FEC • Transform a prioritized MR bit-stream to non-prioritized MD (Multi-Description) stream with additional redundancy (using FEC)

12. MD-FEC Transcoder • Step 1: • Partition a MR bit-stream to N layers and split the ith layer into i equal parts R0 R1 R2 Ri-2 Ri-1 RN-2 RN-1 … … 2 3 … i … N 1 1 2 3 … i-1 i

13. MD-FEC Transcoder • Step 2: • Adopt (N, i, N-i+1) Reed-Solomon code to the ith layer and form N packets as follows: 1 2 … i … N Packet 1 FEC 2 … i … N Packet 2 . . . FEC FEC … i … N Packet i FEC FEC … FEC … N Packet i+1 . . . FEC FEC … FEC … N Packet N

14. MD-FEC Transcoder • Optimization on Ri, i=0…N • Notations: • qi(N) : probability that i+1 out of N packets are delivered to the destination • D(r) : Distortion function of rate r Distortion … Rate … R0 R1 Ri RN-1

15. MD-FEC Transcoder Cont’ • Problem statement: • Minimize the expected distortion ED: • E is the distortion encountered when the source is represented by zero bits

16. MD-FEC Transcoder Cont’ • The total rate Rt equals: • Thus constraints to the optimization problem are:

17. Performance Summary • Simulations have been done to show the variation of sending rate and PSNR upon variation in network capacity and random losses • MD-FEC can maintain a smooth PSNR • LIMD/H can adapt to the variation of network bandwidth quickly while reducing the rate fluctuation induced by random losses and channel probing

18. Discussion • The MD-FEC is a novel technique to add robustness to many layer coding schemes • LIMD/H congestion control mechanism can provide low variation in transmission rate while guaranteeing inter-traffic fairness • However, the delay caused by explicit end-to-end feedback and FEC operations may affect the performance of the system