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
Agenda
Introduction
 LIMD/H Congestion Control
 MD-FEC Transcoder
 Performance Summary
 Discussion

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
Introduction

Two questions:


How to control the transmission rate?
How to control the video source to adapt to the
transmission rate?
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)
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
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
LIMD/H Congestion Control
MD-FEC Transcoder

Layered or Multi-Resolution (MR) source
coding is a common coding method to
provide quality/bit-rate scalability
Raw Video Stream
Multiresolution
(MR)
Source Coder
..
Base Layer
Enhancement Layer 1
Enhancement Layer 2
Enhancement Layer N
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
MD-FEC Transcoder

MD-FEC

Transform a prioritized MR bit-stream to nonprioritized MD (Multi-Description) stream with
additional redundancy (using FEC)
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
2
3
i
…
1
2
RN-1
…
…
1
RN-2
3
N
…
…
i-1
i
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
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
R0 R1 … Ri … RN-1
Rate
MD-FEC Transcoder
Cont’

Problem statement:


Minimize the expected distortion ED:
E is the distortion encountered when the source is
represented by zero bits
MD-FEC Transcoder
Cont’

The total rate Rt equals:

Thus constraints to the optimization problem are:
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

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 endto-end feedback and FEC operations may
affect the performance of the system
