Zurich Research Laboratory LCN ‘03 | 22. October 2003 | Bonn / Königswinter Presentation...

Zurich Research Laboratory

LCN ‘03 | 22. October 2003 | Bonn / Königswinter www.zurich.ibm.com

Roman Pletka, Marcel Waldvogel and Soenke Mannal (University of Stuttgart)

PURPLE: Predictive Active Queue ManagementUtilizing Congestion Information

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Purple: Predictive AQM Utilizing Congestion Information | LCN ‘03 © 2003 IBM Corporation

Overview

The goals of AQM• AQM based on queue level occupancy

• Rate-based AQM

• Per-flow AQM Explicit congestion notification (ECN) RFC 3168

• Measurements from real Internet backbones The Purple algorithm

• The macro-managed part

• The micro-managed part Simulation results

• The single-bottleneck case

• The multi-bottleneck case Conclusion and outlook

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End-to-end Packet delivery Requirements

AQM Goods for End-to-end Packet Delivery:1. Low packet loss rates.2. Short end-to-end delays.3. High TCP goodput.4. Absorb traffic bursts [Villamizar:94] (bandwidth–delay product of

buffer space in routers).5. Stable queuing delays.6. 4 Packets / connection in Flight [Morris 97].

Non Goals:1. Queues stabilized at a certain length.2. Exact per-flow fairness.3. Keeping per-flow state information.

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United Colors of AQM

RED[Floyd 93]

PURPLE

Tail DropA-RED[Floyd 01]

S-RED[Feng 99]

F-RED[Lin 97]

BLUE [Feng 99]

Time

BAT[Bowen 01]

Green 1[Feng 02]

Green 2[Wydrowsky 02]

non lin.RED

[Plasser 02]

Kantawala &Turner

D-RED[Aweya 01]

Flow-based

Based on intrinsic TCP properties

Rate-based

Heuristics

PI Controller[Hollot 01]

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Explicit Congestion Notification (ECN)

Explicit congestion notification (ECN) standardized in [RFC3168], first discussed in context of the DECbit in [Ramakrishnan 90].

ECN enables to indicate congestion without dropping packets and causing a later retransmit or time-out. Done at routers by simply setting a mark in the packet header when a packet would have been dropped but there is still space in the queue.

ECN does not require routes to be symmetric. The concept has the potential to significantly improve latency and

goodput, but current AQM mechanisms such as RED [Floyd 93] often need to revert to packet loss.

Improvements in throughput and goodput when using ECN have been reported in RFC2884.

Although ECN is not widely deployed yet today but can be expected to be widespread in the future:Today: 2.3% of ECN-enabled traffic found in an OC-12c Packet-over-Sonet link connecting the Merit premises in East Lansing to the Internet2/Abilene.

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Purple: The Static Model…

TCP steady state equation from [Mathis 97] of a single TCP connection n:

nn

nnn

pR

ScX

• From a single connection to a bundle:

a system constantMaximum segment sizeRound trip timeProbability of a “packet loss”

cn

Sn

Rn

pn

nn

nnn

pR

ScX

Static Model:• Scaling the bandwidth of a single TCP connection by a factor :

pR

ScN

pRSc

pR

ScX

N

n nn

N

n nn

nn

11

1

• Scaling the bundle: e

pR

ScNX

2

1

N

nnee

1

0

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Purple: …and its Dynamics

Splitting the drop probability:

Control rule:

kkk pppR

ScNX

Router kRouter 1 Router K

2p

p

kkk ppp

p 2

Ratio of packetswith CE set

Ratio of packetswith CWR set

Obtained frompk and p<k, recorded from the preceding RTT

Source Receiver

Assumption: - k is the main bottleneck and drop probabilities are small.=> summing is a good approximation.

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RTT estimation

Maintain a distribution of measured RTTs (array of 32 values) Estimation:

• Add an exact-match packet filter when CE bit is set.

• Measure time until a packet with CWR arrives for this classifier. Ignore shortest and longest values measured. This can be smartly achieved on network processors.

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Purple: Microscopic Drop Probability Updates

Enhancement to short term queue variations by using a fine-grained microscopic part and taking into account the average queue length.

)1( Qq

LX

Link capacityqueuing delay parameterAverage queue occupancyTotal queue capacity

LqQ

kkk ppp

p 2

kkk ppL

Xpp

2

2

kkk ppQq

pp

2))/1((

1

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Purple: Putting it all together

At packet arrival: Background task:

if ecn_enabled(pkt) thenmeasure_ce_probability();measure_cwr_probability();if rand() ≤ pk then

set_ce(pkt);start_rtt_est(pkt);

end ifend ifif Queue full then

drop(pkt);return;

end ifenqueue(pkt);

ewma(q);ewma(X);remove_expired_rtt_entries(rtt_max); L / X’ ;p’k p/2 – p<k – p>k ;if t > --rtt_cntr then

update p<k from history;update p>k from history;update RTT estimate R;p p/2 ;rtt_cntr floor(R/t);

end if

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The Single-Bottleneck Case

Router

TCP Source

TCP Sink

Purple Queue

Source 1

Source n

100 Mbps / 2 ms

100 Mbps10-20 ms

Sink n

100 Mbps10-20 ms

Sink 1

Simulation Parameters:

thmin =10 packetsthmax = 600 packetspmax = 0.02wq = 0.002 All AQM schemes are ECN enabled.

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Rate and Goodput Comparison

93

94

95

96

97

98

99

100

2 4 6 8 10 12 14 16 18 20

Mean queuing delay [ms]

Rat

e [m

bp

s]

PURPLE 10-80 sourcesARED 10-80 sourcesRED 10-80 sources

93

94

95

96

97

98

99

100

2 4 6 8 10 12 14 16 18 20


Rat

e [m

bp

s]

PURPLE 10-80 sourcesARED 10-80 sourcesRED 10-80 sources

Rate Goodput

8010

10

10

80

80 80

10

1010

80

80

Results with the micro-managed part disabled.

Not enough sources for good parameter estimation!

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Comparison of Mark and Drop Rates

0

5000

10000

15000

20000

25000

30000

35000

10 20 30 40 50 60 70 80 90 100

Number of TCP sources

Pac

ket

dro

ps/

mar

ks [

Byt

es]

PURPLE marked

PURPLE dropped

ARED marked

ARED dropped

RED marked

RED dropped

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Goodput and Delay Comparison

88

90

92

94

96

98

100

1 1.5 2 2.5 3 3.5 4 4.5 5


Go

od

pu

t [m

bp

s]

PURPLE with a=8PURPLE with a=4PURPLE with a=2PURPLE with a=1REDARED

Results with the micro-managed part and shorter queues.

10 Sources 100 Sources

10 Sources

100 Sources

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Average Queue Length and Local Drop Rate

REDPURPLE ARED

- 100 TCP Sources

Que

ue L

engt

h (k

B)

Dro

p P

roba

bilit

y

Simulation Time [s]0

160

100 0 100 0 100

0 1000 1000 100

0

160

0

160

0

0.14

0

1

0

1

0

Simulation Time [s] Simulation Time [s]

Simulation Time [s] Simulation Time [s] Simulation Time [s]

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Source 1:1

Purple

Router

TCP Source

TCP Sink

Purple Queue

The Multi-Bottleneck Case

Source 1:n

100 Mbps

Source 2:1

Source 2:n

Source 3:1

Source 3:n

Sink 2:1

Sink 2:n

Sink 3:1Sink 3:n

Sink 1:n

Sink 1:1

10 ms100 Mbps20 ms

100 Mbps10 ms

100 Mbps1 ms

100 Mbps1 ms

100 Mbps10-20 ms

100 Mbps10-20 ms

100 Mbps10-20 ms

100 Mbps10-20 ms

100 Mbps10-20 ms 100 Mbps

10-20 ms

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The Multi-Bottleneck Case

0

200

400

600

800

1000

1200

1400

1600

1800

10 20 30 40 50 60 70 80 90 100

Number of TCP Sources

Nu

mb

er o

f R

TO

Tim

eou

ts

Bundle 1: PURPLE

RED

ARED

Bundle 2: PURPLE

RED

ARED

Bundle 3: PURPLE

RED

ARED

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Conclusion Purple is an AQM scheme designed for ECN-enabled TCP/IP

networks. Improved TCP goodput by taking into account the steady state

properties of TCP. Purple maintains low buffer usage even with a high number of TCP

connections and therefore improves the end-to-end delay. Significant less packet drops than other well-known AQM algorithms. Faster convergences of AQM parameters lead to more stable drop

probabilities lead to less tail drops.

Outlook Possibility to maintain per-incoming interface RTT estimates. Provides new means for TCP bandwidth estimation and its

characteristics (short-lived vs. long-term sessions).

Zurich Research Laboratory LCN ‘03 | 22. October 2003 | Bonn / Königswinter Presentation...

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Transcript of Zurich Research Laboratory LCN ‘03 | 22. October 2003 | Bonn / Königswinter Presentation...