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NADA: A Unified Congestion Control Scheme

for Real-Time Media

Xiaoqing Zhu and Rong Pan

Advanced Architecture & Research

Cisco Systems

August 2012

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Agenda

• Design goals

• System model

• Network node operations

• Sender/Receiver behavior

• Evaluation results

• Open issues

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Design Goal #1:Limit Self-Inflicted Delay

network queue network queue

Time

Congest

ion

win

dow

Siz

e

Packet loss

Time

Rate

React early

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Design Goal #2:Leverage A Suite of Feedback

Mechanisms

Delay-based ECN-based

PCN-based

none existing feature

new feature

Network Support

Perf

orm

an

ce

Existing loss-basedschemes

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Design Goal #3:Weighted Bandwidth Sharing

Relative bandwidth

Application-level priority

Bandwidth sharing among flows:

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video playout

optimal rate calculation

encoderrate control

RTCP report

video packets

network node

measure delay/marking

sender receiver

target rate

update networkcongestion notification

System Overview

rate shaping buffer

bufferlevel

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Network Node Behavior

• Queuing discipline: FIFO

• Congestion notification via:

Delay: no special operation at the queue

ECN: queue-based random marking

PCN: token-bucket-based random marking

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Queue-based ECN Marking

if :

no marking

else if :

else:

mark all packets

update: Avg. Queue OccupancyM

ark

ing P

robabili

ty

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Token-bucket-based PCN Marking

upon packet arrival:

meter packet against token bucket ;

update token level

if :

no marking

else if :

else:mark all packets

Remaining Token BucketM

ark

ing P

robabili

ty

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target rate

Sender Structure

target rate calculation

encoderrate control

video packets

rate shaping buffer

sending rate calculation

RTCP report(loss/delay/ECN/PCN)

bufferlevel

videorate

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Target Rate Calculation

• Reacting to delay: session priority

queuing delay

marking ratio

• Reacting to ECN/PCN marking:

scaling parameter

scaling parameter

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Sending Rate Calculation

• Accommodate lag in encoder reaction

• Trade-off between between network queuing and rate shaping delay

scaling parameter

encoder reaction time

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Slow-Start Rate

start time

time horizon

Time

Rate

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Receiver Behavior

• Observe instantaneous end-to-end per packet statistics:

Queuing delay:

ECN/PCN marking:

• Obtain time-smoothed estimations:

• Periodic RTCP reports (e.g., at 3% of received packets)

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Test Scenario

• Bottleneck bandwidth: 30Mbps

• Random delay measurement error for stream 6, at time t=30s

Flow ID

1 1 2 1

2 1 2 1

3 2 6 1

4 2 6 2

5 3 5 2

6 3 5 2

7 2 4 3

8 2 4 3

9 3 6 3

10 3 6 3

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Delay-Based Adaptation: Per-flow Rate

Stream 6 delay measurement error

Weighted BW sharing

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Delay-Based Adaptation: Total Rate

Fast convergence

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Delay-Based Adaptation: Bottleneck Queue

Low standing queue

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Delay-Based Adaptation: Packet Loss Ratio

No persistent losses

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Delay vs. ECN: Per-Flow RateECN-BasedDelay-Based

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Delay ECN

Delay vs. ECN: Bottleneck Queue

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ECN vs. PCN: Per-Flow RateECN PCN

Smoother streaming rates

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ECN vs. PCN: Total RateECN PCN

Slight under-utilization

No losses

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ECN PCN

ECN vs. PCN: Bottleneck Queue

Zero standing queue

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Conclusions and Next Steps

• Key benefits of NADA: Fast rate adaptationWeighted bandwidth sharingCan work with a range of congestion signalsIn case of PCN: zero standing queue and smoother streaming rates

• Next steps: Future evaluations in linux-based implementationsGraceful transition between different congestion signalsCompete robustly against loss-based schemes