The Effects of Active Queue
Management on Web Performance
Annual Conference of the Special Interest Group on Data
Communication (SIGCOMM 2003)
August 25-29, 2003
Karlsruhe, Germany
Presentation: Andreas Haeberlen
COMP629, February 26, 2004
© 2004 Andreas Haeberlen, Rice University
Long Le
Jay Aikat
Kevin Jeffay
F. Donelson Smith
Dept. of Computer Science
University of North Carolina
(Chapel Hill)
1
Who would you believe?
David Clark (MIT)
81-89: Internet Chief Protocol Architect
Bruce Davie (Cisco)
MPLS
Kevin Jeffay (UNC)
Real time (YARTOS), QoS, Multimedia
?
Deborah Estrin (UCLA)
Multicast routing, BGMP, ...
Sally Floyd (ICIR)
F. Donelson Smith (UNC)
Pushback, ECN, High-speed TCP, TFRC, ...
Andrew, SNA, FAPL
Larry L. Peterson (Princeton)
Scout, TCP Vegas, x-Kernel...
Craig Partridge (UCLA)
RTP, Gigabit Networking
?
"AQM is useless without ECN"
-- this paper
© 2004 Andreas Haeberlen, Rice University
Scott Shenker (ICSI)
CAN, RSVP, ALM, ...
"Thou shalt use AQM"
-- RFC2309
2
Introduction
Host


X

Router


© 2004 Andreas Haeberlen, Rice University
Internet uses packet
switching
 Need queues to
handle bursts
Queues are of finite
length
 Drop packets when
queue is full
Overload can lead to
congestion collapse
Solution: Congestion
control mechanism
AIMD extension for TCP
3
Introduction: RED


X

min max
pdrop
Average queue
length
© 2004 Andreas Haeberlen, Rice University

Problems with 'drop tail':
 High packet loss
 Full queue  latency
 Lockout
Idea: Drop some packets
before queue is full to
trigger AIMD mechanism
Short bursts should still
be tolerated!
RED: Use average queue
length (EWMA) to
compute drop probability
4
Introduction: ARED, PI, REM
min max
pdrop

1.0

0
Average queue
length

RED:
pb 
max P (avg  min th )
max th  min th
PI:
p(kT )  a  (q(kT )  qref )  b  (q(( k  1)T )  qref )  p(( k  1)T )

REM:
p(t )  max( 0, p(t  1)    (  (q(t )  qref ))  x(t )  c))
© 2004 Andreas Haeberlen, Rice University

RED improvements:
 Gentle mode
 Adaptive RED (ARED)
Many other variants;
>50 proposed in 1999!
Biggest problem: RED is
either unstable or
responds too slowly
Application of control
theory: Proportional
integrator (PI)
Random exponential
marking (REM)
5
Introduction: ECN

4
IP
header
IHL DSCP
Length
flags
16-bit ID
Fragm. offset
Protocol
Checksum
TTL
Source IP
Destination IP

Data
...
TCP
header
Offset
Flags

TCP Window
...
Sender
ECE:
Echo CE
© 2004 Andreas Haeberlen, Rice University
Receiver

Idea: Mark packets
instead of dropping them
Explicit congestion
notification (ECN)
Special bits in IP and
TCP headers
Effect: Send window is
reduced
CE: Congestion
Experienced
CWR: Congestion
Window Reduced
6
Goal of this paper


Study the effects of active queue
management on the response times
experienced by web users
Compare ARED, PI, REM with/without ECN
© 2004 Andreas Haeberlen, Rice University
7
Methodology
FreeBSD machines
(ARED, PI, REM)
Traffic
generator
Server



Network models interconnection between two ISPs
Traffic generators emulate browsing users
Offered load varied between 80%-105% of bottleneck
© 2004 Andreas Haeberlen, Rice University
8
Cumulative probability
Results: 80% load, no ECN
Response time (ms)



Offered load: 80% of bottleneck link (100Mbps)
Result 1: For offered loads up to 80%, AQM does not
provide better response time than drop-tail FIFO
Result 2: ARED even decreases performance!
© 2004 Andreas Haeberlen, Rice University
9
Cumulative probability
Results: 90% load, no ECN
Response time (ms)



Offered load: 90% of bottleneck (98%, 105% similar)
Result 1: For 80% of the responses, PI, REM and
drop-tail all provide reasonable performance
Result 2: In the remaining cases, PI is better
© 2004 Andreas Haeberlen, Rice University
10
Cumulative probability
Cumulative probability
Results: 98% load, with ECN
Response time (ms)



Response time (ms)
Offered load: 98% of bottleneck
Result 1: With ECN, both PI and REM significantly
improve response time at offered loads >90%
Result 2: Response time with ARED is consistently poor
© 2004 Andreas Haeberlen, Rice University
11
Summary and Conclusions


Major results:
 Up to 80% load, drop-tail is as good as AQM
 Without ECN, PI is slightly better than ARED, REM
 With ECN, both PI and REM improve response
times significantly at 90% load and above
 ARED consistently performs poorly, even with ECN
Conclusions:
 AQM without ECN: Small improvement
 AQM with ECN: Significant improvement - good
enough to operate links at near saturation levels!
© 2004 Andreas Haeberlen, Rice University
12
Review



Sound: Realistic experiments, good results,
well presented
Relevant: Shows a way for providers to get
better link utilization (ECN-capable routers)
Interesting: Results for RED inconsistent with
its high reputation in the community
© 2004 Andreas Haeberlen, Rice University
13
The End
Rebuttal
© 2004 Andreas Haeberlen, Rice University
14
80% Uncongested


Argument: Queue management in an
uncongested network is not very
interesting
Purpose is to show what the interesting
case is
© 2004 Andreas Haeberlen, Rice University
15
ECN helps over 90%




Argument: PI paper already has that result
Paragraph of prose is not a proof
Popular belief about ARED shows that
intuition is sometimes misleading
What is new? - Experimental validation
© 2004 Andreas Haeberlen, Rice University
16
"Everybody loves RED"


May, M., Bolot, J., Diot, C., and Lyles, B., Reasons not to deploy RED, technical report,
June 1999.
"The main results we found were, first, that RED with small buffers does not improve
significantly the performance of the network... Second, parameter tuning in RED remains an
inexact science, but has no big impact on end-to-end performance."
M. Christiansen, K. Jeffay, D. Ott, and F.D. Smith, Tuning RED for Web Traffic, ACM
SIGCOMM, August 2000.
"We conclude that for links carrying only web traffic, RED queue management appears to
provide no clear advantage over tail-drop FIFO for end-user response times... There are
some limitations of this study that should be considered... Congestion on both paths on a
full-duplex link and over multiple router hops should also be considered."
© 2004 Andreas Haeberlen, Rice University
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ARED is bad




Argument: Goal is link utilization, stabilize
queue delay
Stable, but high queue delay is not desirable
Argument: Web traffic results were already
published in SIGCOMM 2000
Best paper award for stale results?!?
-> See conspiracy theory slide
© 2004 Andreas Haeberlen, Rice University
18
RED Deployment




Argument: Would Cisco deploy it without
proof that it works?
If IETF can make an error, so can Cisco
Huge companies have made huge mistakes:
 Microsoft and the Internet
 IBM and microkernels
Proof by Credibility
© 2004 Andreas Haeberlen, Rice University
19
RED Parameter Setting




Argument: Need more research on parameter
setting
Many papers have been written on RED - lack
of research?
There are even summary papers on the
family of RED techniques!
Even RED authors do not have good
recommendations
© 2004 Andreas Haeberlen, Rice University
20
Evaluating RED



Argument: RED was designed for something
else
Question: Which metrics matter?
Delay for interactive applications certainly
matters!
© 2004 Andreas Haeberlen, Rice University
21
"Experiment is unrealistic"



Web traffic only
 Focus is response time; web surfing is the
dominant interactive application
Network too small
 Need controlled evironment
 Access to backbone routers?
Configuration error
 Careful calibration; built on previous work
 Much better than in pro-RED papers
© 2004 Andreas Haeberlen, Rice University
22
PI is cool

Not the main point of the paper - really
advocates use of ECN (if you read between
the lines)
© 2004 Andreas Haeberlen, Rice University
23
"ECN is not yet deployed widely"


Not true - newer OSes do have support for it
Paper breaks the 'vicious circle of deployment'
by providing a good case for ECN
© 2004 Andreas Haeberlen, Rice University
24
Conspiracy: Best paper award



Did SIGCOMM PC conspire against RED?
Is that plausible, given the list of names on
the RED RFC?
How is best paper decision made?
© 2004 Andreas Haeberlen, Rice University
25
The End
Backup
© 2004 Andreas Haeberlen, Rice University
26
"Experimental error"

"Usually, there were no noticeable differences
between repetitions; where there were..."
 Unrealistic to assume that results from an
experiment of this size can be reproduced exactly
© 2004 Andreas Haeberlen, Rice University
27
"Experimental error" II

"We chose two target queue lengths..." - "a queue
size ... that would represent a 'best practice' choice"
 They did try other parameters
 Many other authors complain that choosing
parameters for DT/RED is not an 'exact science'
© 2004 Andreas Haeberlen, Rice University
28
"Experimental error" III


"This is an artifact of our traffic generation model
wherein browsers generate requests less frequently
as response time increases"
 Is this really unrealistic?
 Applies only to 105% results; main points can be
demonstrated at 90%/98%
"The exact reasons for the observed differences
remains the subject of continued study."
© 2004 Andreas Haeberlen, Rice University
29
"Experimental error" IV

"The exact reasons for the observed differences
remains the subject of continued study."
© 2004 Andreas Haeberlen, Rice University
30
"AQM method X performs better"

AQM design space is large
© 2004 Andreas Haeberlen, Rice University
31
"What about other protocols?


TCP/IP is the dominant protocol in the
internet today
ARED and the other AQM schemes were
specifically designed for TCP/IP
© 2004 Andreas Haeberlen, Rice University
32