7/28/2019 My RED

1/26

Advanced Computer

Networking

Active Queue Management

7/28/2019 My RED

2/26

TCP & AQM

xi(t)

pl(t)

TCP:

Reno Vegas

AQM:

DropTail RED REM,PI,AVQ

Example congestion measure pl(t) Loss (Reno)

Queuing delay (Vegas)

2 behnam shafagaty

7/28/2019 My RED

3/26

Active queue management

Main idea:: provide congestioninformation by some indications.

Issues How to measure congestion?

How to feed back congestion info?

3 behnam shafagaty

7/28/2019 My RED

4/26

Active Queue Management

Goals: Theprimary goal is to provide congestion

avoidance by controlling the average queuesize such that the router stays in a region oflow delay and high throughput.

To avoid global synchronization (e.g., in TahoeTCP).

To control misbehaving users (this is from afairness context).

4 behnam shafagaty

7/28/2019 My RED

5/26

Algorithm 1: Drop Tail

5

FIFO queuing mechanism that dropspackets from the tail when the queueoverflows.

Introducesglobal synchronizationwhenpackets are dropped from severalconnections.

behnam shafagaty

7/28/2019 My RED

6/26

6

Early Random Drop Router

If the queue length exceeds a drop level, then

the router drops each arriving packet with a

fixed drop probabilityp.

Reduces global synchronization

Does not control misbehaving users (UDP)

p

Dr op level

behnam shafagaty

7/28/2019 My RED

7/26

RED/ECN Router Mechanism

7

1

0

AverageQueue Length

minth maxth

Dropping/MarkingProbability

Queue Size

maxp

behnam shafagaty

7/28/2019 My RED

8/26

RED Algorithm

for each packet arrival

calculate the average queue size avg

if minth avg< maxthcalculate the probabilitypawith probability pa:

mark the arriving packet

else if maxth avgmark all the arriving packet.

behnam shafagaty8

7/28/2019 My RED

9/26

behnam shafagaty9

avg - average queue length

avg=(1wq)xavg+wqxq

whereqis the newly measured queue length.

This exponential weighted moving averageisdesigned such that short-term increases inqueue size from bursty traffic or transient

congestion do not significantly increaseaverage queue size.

7/28/2019 My RED

10/26

behnam shafagaty10

REDdrop probability (pa)

pb = maxp x (avg - minth)/(maxth minth)

then

pa = pb/ (1 - count x pb)

Where, count is number of consecutive

packets queued since last discard whilein the critical region.

7/28/2019 My RED

11/26

RED parameter settings

wqsuggest 0.001

7/28/2019 My RED

12/26

Packet-marking probability

The goal is to uniformly spread out the markedpackets. This reduces global synchronization.

Method 1: geometric random variable

When each packet is marked with probabilitypb,, the packet inter-marking time, X, is ageometric random variable with E[X] = 1/pb.This distribution will both cluster packetdrops and have some long intervals betweendrops!!

12 behnam shafagaty

7/28/2019 My RED

13/26

packet-marking probability

Method 2: uniform random variable

Mark packet with probability

pb/ (1 - countxpb)where countis the number of unmarked

packets that have arrived since last

marked packet.

13 behnam shafagaty

7/28/2019 My RED

14/26

14

Method 1: geometric p = 0.02

Method 2: uniform p = 0.01Result :: marked packets more clustered for

method 1 Uniform is better at eliminatingbursty drops

behnam shafagaty

7/28/2019 My RED

15/26

Setting maxp

RED performs best when packet-markingprobability changes fairly slowly as theaverage queue size changes.

This is a stability argument in that the claim isthat RED with small maxpwill reduce oscillationsin avgand actual marking probability.

They recommend that maxpnever be greater

than 0.1{This is not a robust recommendation.}

behnam shafagaty15

7/28/2019 My RED

16/26

Variant: ARED (Feng, Kandlur, Saha, Shin 1999)

Motivation: RED extremely sensitiveto #sources

Idea: adapt maxp to load If avg. queue < minth, decrease maxp If avg. queue > maxth, increase maxp

No per-flow information needed

17behnam shafagaty

7/28/2019 My RED

17/26

Variant: FRED (Ling & Morris 1997)

Motivation: marking packets in proportion to flow rate isunfair (e.g., adaptive vs unadaptive flows)

Idea:

A flow can buffer up to minq packets without being

marked A flow that frequently buffers more than maxq

packets gets penalized

All flows with backlogs in between are marked

according to RED No flow can buffer more than avgcq packets

persistently

Need per-active-flow accounting18

behnam shafagaty

7/28/2019 My RED

18/26

Variant: SRED (Ott, Lakshman & Wong 1999)

Motivation: wild oscillation of queue inRED when load changes

Idea:

Estimate number Nof active flows An arrival packet is compared with a randomly

chosen active flows

N~ prob(Hit)-1

cwnd~p-1/2and Np-1/2= Q0impliesp = (N/Q0)2

No per-flow information needed

19behnam shafagaty

7/28/2019 My RED

19/26

Variant: BLUE (Feng, Kandlur, Saha, Shin 1999)Idea: perform queue management based

directly on packet loss and link utilizationrather than on the instantaneous oraverage queue lengths.

20behnam shafagaty

7/28/2019 My RED

20/26

REM (Athuraliya & Low 2000)

Congestion measure: pricepl(t+1) = [pl(t) + g(albl(t)+ x

l(t) - cl)]

+

Embedding: exponential probability function

Feedback: dropping or ECN marking

0 2 4 6 8 10 12 14 16 18 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Link congestion measure

Lin

kmarkingprobability

21behnam shafagaty

7/28/2019 My RED

21/26

Match rate

Key features

Clear buffer and match rate

Clear buffer

)])()(()([)1( ll

llll ctxtbtptp

)()( 11 tptp sl

Sum prices

22

behnam shafagaty

7/28/2019 My RED

22/26

TCP/AQM Models

behnam shafagaty

7/28/2019 My RED

23/26

TCP & AQM

xi(t)

pl(t)

Example congestion measurepl

(t)

Loss (Reno)

Queueing delay (Vegas)

26

behnam shafagaty

7/28/2019 My RED

24/26

Macroscopic View of TCPControl

TCP/AQM: A feedback control systemTCP Sender 1

C

xi(t)

TCP:

Reno

Vegas FAST

AQM:

DropTail / RED Delay ECN

TCP Sender 2

q(t)

TCP Receiver 1

TCP Receiver 2

Bii tq,txFtx

ctxtqGtq Fi

i ,

F

B

27behnam shafagaty

7/28/2019 My RED

25/26

Fluid Models

Assumptions:

TCP algorithms directly control the transmission

rates; The transmission rates are differentiable (smooth);

Each TCP packet observesthe same congestionprice(loss, delay or ECN)

Bii tq,txFtx

ctx,tqGtq F

ii

28behnam shafagaty

7/28/2019 My RED

26/26

Outline

Protocol (Reno, Vegas, RED, REM/PI)

Equilibrium

Performance Throughput, loss, delay

Fairness Utility

Dynamics

Local stability Cost of stabilization

))(),(()1(

))(),(()1(

txtpGtp

txtpFtx

29

behnam shafagaty