Transmitting scalable video over a diffserv network
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Transmitting Scalable Video over a DiffServ network . EE368C Project Presentation Sangeun Han, Athina Markopoulou 3/6/01. Project Proposal. Problem: Video transmission over the heterogeneous Internet Facts:

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Transmitting Scalable Video over a DiffServ network

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Transmitting scalable video over a diffserv network

Transmitting Scalable Video over a DiffServ network

EE368C

Project Presentation

Sangeun Han, Athina Markopoulou

3/6/01


Project proposal

Project Proposal

  • Problem:

    • Video transmission over the heterogeneous Internet

  • Facts:

    • Scalability: different parts of a video stream contribute unequally to the quality.

    • DiffServ Networks can provide service differentiation, based on the marking of packets.

  • Proposal

    • Limit the effect of loss when it happens. Prioritize information according to importance and drop packets accordingly.


Specifics

conditioning

classification

AF11

Specifics

  • What type of scalability? H.263+, SNR

  • Which DiffServ class? AF (priority dropping)

EI

EP

EP

EP

EL

BL

I

P

P

P


Simulation scenario

Simulation scenario

Main stream: Foreman (10fps) 136Kbps, BL+EL, 2min

10-20 Interfering Streams

BL+EL~=136Kbps

random parts of 6 different streams

Single AF queue,

2 levels, 100KB

1.5Mbps

H.263+

Encoder

+

Layering

RTP

Packet.

for H.263

(*)

Depackt.

Decoding+

[Error

Conceal.] (**)

Marker

Loss info

(*) Mode A: at frame level,

Total header= IP(20)+UDP(8)+RTP(12)+H.263(4)=44B

Original Stream

(**) Freezing previous frame


Objective of the project

Objective of the Project

  • Show the benefit from using Priority Dropping for Scalable Video

    • MUX gain

    • Graceful Quality Degradation

    • Handle short term congestion

  • Configuration

    • AF queue:

      • buffer management, thresholds, other parameters

    • Layering parameters

      • base layer, temporal dependence

  • Recommendation

    • To Feedback or to Drop?


Mux gain

MUX gain

Layered+PD

Nonlayered


Graceful degradation with loss

FGS

+ data loss

Graceful degradation with loss

NL, no loss

Layered+loss

Non Layered + loss


Short term congestion

Rate

Congestion

EL

BL

time

R

Reaction with no delay D=0

time

D

D

Reaction with Delay D>0

time

Short Term Congestion

  • The source may react to congestion by adapting its transmission rate...


Reaction time vs congestion duration

Reaction time vs.congestion duration

  • Simple example:

    • 10 streams + 5 more in [55sec,65sec]

    • 10 streams react by dropping their EL in [55+D, 65+D]


Heavier congestion

Heavier congestion

  • Heavy + non adaptive interfering traffic:

    • 10 streams + 10 more in [55sec,65sec]

    • 10 streams react by dropping their EL in [55+D, 65+D]


Priority dropping vs feedback

Rate

Congestion

R(t)

EL

BL

time

Priority dropping vs Feedback

  • Feedback

    • is limited by delay

    • saves network resources

    • requires coordination

  • Priority Dropping

    • is like reaction in D=0, by appropriate rate decrease

    • may handle non adaptive sources


Configuration of af queue

BL - low drop precedence

EL - high drop precedence

Drop

prob

High drop

Low drop

1

0

Buffer occupancy

L_min

L_max

H_min,max

Configuration of AF queue

  • Choices:

    • Thresholds for the different priorities

    • Buffer management: RED or DropTail?

  • Observations:

    • Not sensitive to choice of thresholds

    • RED inappropriate: do not use Avg Qsize, set Lmin=Lmax

    • Differentiation: (I) different thresholds (II) Occupancy


Red worse than droptail

RED worse than DropTail

For all loads….

and

…for all thresholds


Threshold for el hp

Threshold for EL(HP)

  • By assigning the buffer thresholds

    • we control the Queue Occupancy for BL, EL

Threshold_HDP = 56

Threshold_HDP = 16


Threshold for el lp

Threshold for EL(LP)

  • …this way we distribute the loss among BL and EL

  • ….and thus the quality

  • Insensitive to:

    • RED, DropTail

    • BL choice

    • [more sensitive to load]


Effect of bl i on quality degradation

QP(BL)=12, 1:1, (BL=64kbps:EL=74kbps)

QP(BL)=15, 1:2, (BL=50kbps:EL=86kbps)

QP(BL)=30, 1:4, (BL=27kbps:EL=110kbps)

Same target rate: BL+EL~=136kbps

Effect of BL (I): on quality degradation


Effect of bl ii on thresholds

QP(BL)=12, 1:1, (BL=64kbps:EL=74kbps)

QP(BL)=15, 1:2, (BL=50kbps:EL=86kbps)

QP(BL)=30, 1:4, (BL=27kbps:EL=110kbps)

Same target rate: BL+EL~=136kbps

Effect of BL (II): on thresholds


Transmission of scalable video

Transmission of Scalable Video

  • Use feedback + adaptation at the source to match the transmission rate with the bottleneck bandwidth, to save network resources along the path

  • Use Priority Dropping to handle short term congestion

Quality

Feedback

BL2

BL1

PD

Rate

loss


Future work

Future work

  • Improvements needed

    • realistic feedback + adaptation

    • >2 layers

    • finish FGS

  • New experiments needed

    • Delay aspect:

      • Loss at the playback buffer

      • Entire streams having different delay requirements

    • Multiple hops

    • Single wireless hop (802.11 + QoS)

    • Video + Data

    • Larger Bandwidths

    • Other types of scalability: FGS, Temporal, Spatial, DP


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