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Modeling the Effect of a Rate Smoother on TCP Congestion Control Behavior

Kang Li, Jonathan Walpole, David C. Steere

{kangli, walpole, steere}@cse.ogi.edu

Department of Computer Science and Engineering

Oregon Graduate Institute

Molly H. Shor

shor@ece.orst.edu

Department of Electrical and Computer Engineering

Oregon State University

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SenderReceiver

TCP

Data Packets Network

Acknowledgment Packets

Well-known Behaviors of TCP Congestion Control

051015202530354045

0 10 20 30 40 50Time

TCP Transmissio

n RateAvailable bandwidth

• The phase plot for 2 competing TCPs

• The sawtooth figure for an individual TCP

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Trajectories of Various TCP-Friendly Congestion Controls Competing with a TCP

• There exists many limit cycles that oscillate around the equal fair sharing point

• However, we have assumed all the competing flows back off together.– If the assumption is false, they may experience different congestion signals.

– Temporary rate mismatches may lead to non-uniform losses across flows;

– Different network buffering states may affect the timing of packet losses.

A: TCP-friendliness by Varying TCP AIMD Parameters

B:TCP-friendliness by Damping TCP’s Rate Variations

C: An Arbitrary Trajectory that Tracks Around the Fair Share Point

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Modeling Temporary Rate Mismatch

Forward and Wait

Sending Rate Calculated by TCP “Smoothed” Output

Pacing Control

Rate Smoother

Mismatch window (a virtual Buffer)

Buffer Fill-level Rate Adjustment

• We add a rate smoother to TCP to control the rate mismatch: – The pacing period and other control parameters can be tuned.

– Many existed and new pacing and smoothing algorithms can be simulated.

– By tracking a TCP’s throughput, the rate smoother provides an implementation of an Equation-Based TCP-friendly Congestion Control.

• To study the effect of smoothing on TCP, we built a Matlab simulation and a Linux-based implementation.

TCP with a Rate Smoother Component

0+B/2 -B/2

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• Smoothing is simulated based on the following equations:

• TCP congestion avoidance is simulated by:– When no congestion signal

– When congestion signal arrives

Simulation in Matlab

)(

*)(2 tRTT

MSS

dt

tdr

R

Rtr

dt

tdRTT

)()(

)(*)( trtr

dt

trdDtrItrPtr

trtrtr

out

inout

)(*)(*)(*)(

)()()(

Rate Smoother

TCP AIMD

Pacing Control

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Simulation of Two TCPs (one with rate smoother)

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Simulation Results (1) System Plot under Uniform Packet Losses

A B

• Uniform Losses – The same congestion signal for all TCP flows.

• The system trajectory converges to a limit cycle that oscillates around the equal bandwidth sharing point. (Figure A)

– Same phase plot as Figure 3-B with an additional dimension for buffer fill-level.

• The rate produced by AIMD algorithm is used as the input to the rate smoother. (Figure B)

– An alternative would be to use the TCP throughput equation as a function of congestion signals as the input to the rate smoother.

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Simulation Results(2) The Impact of Non-Uniform Packet Losses

• Non-Uniform Losses – Rate-dependent congestion signal for each TCP flow.

• Bandwidth Sharing Ratios depend on loss distributions.– Figures A and B show the backing-off probability and average throughput ratio for a

set of loss distribution models in which a TCP’s backing-off probability P is a function of its current transmission rate r :

– The ratio is close to 1 when the distribution is proportional to the rate (b=1/100) or when it is close to a uniform distribution (b=10).

• Next step: simulate feedback between loss distributions and rate mismatches.

rbearP **1)(

A B

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Conclusion & Future Work

• Conclusion– No big conclusion yet,

– Feedback control based conceptual model and simulation tools lead to clear understanding of TCP congestion control behavior.

– Developed a generic model and implementation of Rate Smoothing based on feedback control.

• Future Work– Simulate feedback between loss distributions and rate mismatches.

– Combine the model with some realistic loss event distributions.

– Extend model from a continuous to a hybrid event-driven system.

– Build a tunable paced TCP implementation that exposes smoothing control parameters to applications.