Adaptive Control for TCP Flow Control

Thesis Presentation

Amir Maor

13/6/02

Presentation Structure

Introduction AdaVegas intuition AdaVegas simulation results Adaptive mechanism for TCP new Reno Conclusion

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Flow Control Existing Solutions TCP NewReno

• The sending rate increases continuously until a packet is dropped.

• Two Phases– Slow Start – increase exponentially– Congestion Avoidance – increase linearly

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NewReno Dynamics

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Flow Control Existing Solutions TCP Vegas

• Stop increasing rate before swamping the network• Delay (propagation delay) + (queuing) Estimates number of queued packets

Decrease Rate Linearly >

Exit >

-<<

Double Rate < Increase Rate Linearly <

Slow StartCongestion Avoidance

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Vegas Dynamics

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Reno And Vegas Dynamics

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Related Work – Chiu & Jain

AIMD converges to stable and fair operating point

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Related Work – Bansal & Barakrishnan

k+l>0; k>=0 or l>=0

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Related Work – Bansal & Barakrishnan

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Related Work – Bansal & Barakrishnan

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Progress

Introduction AdaVegas intuition AdaVegas simulation results Adaptive mechanism for TCP new Reno Conclusion

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How Adaptive Is Vegas?

• Vegas changes the sending rate

• Vegas does not change the way it changes the sending rate

+1 seg/RTT ; -1 seg/RTT ; -0.5*(rate)

• Is this way optimal?

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Linear Increase Constant Optimal Value or Painful Compromise ?

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Making Vegas Adaptive

• The larger the available bandwidth the larger the increase constant

• How do we know how large the available bandwidth is?– We don’t ! BUT we can take a pretty good

guess by using recent history

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Making Vegas AdaptiveAlpha & Beta parameters

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AdaVegas Dynamics0.1Mb/sec

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Vegas_1

Vegas_8

AdaVegas

0.25Mb/sec

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Vegas_1

Vegas_8

AdaVegas

4Mb/sec

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Vegas_1

Vegas_8

AdaVegas

8Mb/sec

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Vegas_1

Vegas_8

AdaVegas

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Progress

Introduction AdaVegas intuition AdaVegas simulation results Adaptive mechanism for TCP new Reno Conclusion

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Simulation Model

• ON/OFF users using heavy tailed distribution• Evaluation criteria:

– Line utilization, queue size,loss rate,fairness

# usersON mean time

Evaluation

criteria

SOURCE1

SOURCE2

SOURCE3

SOURCEN

SINK1

SINK2

SINK3

SINKN

ROUTER1

ROUTER2

300 msec20Mb/sec

1 msec100Mb/sec

1 msec100Mb/sec

SOURCE1

SOURCE2

SOURCE3

SOURCEN

SINK1

SINK2

SINK3

SINKN

ROUTER1

ROUTER2

300 msec20Mb/sec

1 msec100Mb/sec

1 msec100Mb/sec

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Results - UtilizationON mean time

# users

Evaluation

criteria

Utilization High Fair Share

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200 150 100 50 20

ON mean time (OFF mean = 60)

Utili

zatio

n (%

) Vegas_1

AdaVegas

Vegas_8

Utilization Low Fair Share

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200 150 100 50 20

ON mean time (OFF mean = 60)

Utili

zatio

n (%

) Vegas_1

AdaVegas

Vegas_8

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Results – Queue SizeON mean time

# users

Evaluation

criteria

Queue Size Low Fair Share

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200 150 100 50 20

ON mean time (OFF mean = 60)

Queu

e Si

ze

Vegas_1

AdaVegas

Vegas_8

Queue Size High Fair Share

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200 150 100 50 20

ON mean time (OFF mean = 60)

Queu

e Si

ze

Vegas_1

AdaVegas

Vegas_8

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Results – Fairness IndexON mean time

# users

Evaluation

criteria

Fairness Index Low Fair Share

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

200 150 100 50 20

ON mean time (OFF mean = 60)

Fairn

ess

Inde

x

Vegas_1

AdaVegas

Vegas_8

Fairness Index High Fair Share

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

200 150 100 50 20

ON mean time (OFF mean = 60)

Fairn

ess

Inde

x

Vegas_1

AdaVegas

Vegas_8

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Results – Loss RateON mean time

# users

Evaluation

criteria

Loss Rate Low Fair Share

0

0.5

1

1.5

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2.5

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3.5

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4.5

5

200 150 100 50 20

ON mean time (OFF mean = 60)

Lo

ss R

ate

(%)

Vegas_1

AdaVegas

Vegas_8

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Heterogeneous EnvironmentsDifferent RTT

AdaVegas Low Fair Share

9%

23%

68%

None

High RTT

Low RTT

Vegas_1 Low Fair Share9%

22%

69%

None

High RTT

Low RTT

Vegas_1 High Fair Share

63%

7%

30%

None

High RTT

Low RTT

AdaVegas High Fair Share

31%

22%

47%None

High RTT

Low RTT

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Progress

Introduction AdaVegas intuition AdaVegas simulation results Adaptive mechanism for TCP new Reno Conclusion

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Import AdaVegas to NewReno?

• Relation between increase constant and available bandwidth does not hold in NewReno

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NewReno and High Increase Rate

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Congestion Avoidance -Barking up the wrong tree?

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Progress

Introduction AdaVegas intuition AdaVegas simulation results Adaptive mechanism for TCP new Reno Conclusion

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Conclusion & Future Work• AdaVegas is able to adapt better to changing

environments• Research on adaptive mechanisms for

NewReno should focus on “Slow Start” as well

• Develop adaptive mechanism for NewReno• Make AdaVegas’ increase parameter unbound