15744 Course Project 1

Evaluation of Queue Evaluation of Queue Management AlgorithmsManagement Algorithms

Ningning Hu, Liu Ren, Jichuan Chang

30 April 2001

15744 Course Project 2

Motivation

• Typical queuing discipline: DropTail

• Active queue management: – RED (93’), BLUE (99’), …– FRED (97’), SFB (99’), CHOKe (2000’)

• Problem: How to compare them?– Metrics: Utilization, Fairness and Complexity– Method: simulation under common settings

15744 Course Project 3

Algorithms

Drop Tail: drop when the queue is full RED: queue length, minth, maxth, avg

FRED: per-active-flow accounting BLUE: loss rate, link utilization, freeze_time SFB: identify flows using N * L bins CHOKe: compare incoming packet with

random selected packet in queue

15744 Course Project 4

Simulation Scenario

2Mbps

1Mbps, 40ms

2Mbps

UDP

TCP

UDP

TCP

• Topology: Dumb-bell• Metrics: throughput and queue size

source destination

router router

15744 Course Project 5

Drop Tail RED BLUE

FRED SFB CHOKe

TCP

TCP

1. # TCP Flow : # UDP Flow = 10 : 12. UDP sending rate = 2Mbps3. Buffer size = 150 packets

15744 Course Project 6

Performance Comparison

0

0.2

0.4

0.6

0.8

1

0.1 0.2 0.4 0.8 1 2 4 8 UDP Rate (Mbps)

DropTail

RED

FRED

BLUE

SFB

CHOKe

0

50

100

150

0.1 0.2 0.4 0.8 1 2 4 8 UDP Rate (Mbps)

DropTail

RED

FRED

BLUE

SFB

CHOKe

Figure 1. UDP Thpt (Mbps)

Figure 2. UDP Queue Size (packet)

15744 Course Project 7

ConclusionAlgorithm

Link Utilization

FairnessEase of

Configuration

RED Good Unfair Hard

BLUE Good Unfair Hard

FRED Good Fair Easy (adaptive)

SFB Good Fair Easy (non-adaptive)

CHOKe Good Fair Easy (adaptive)

AlgorithmBuffer size

requirementPer-flow State Information

Computational

Overhead

RED Large No Arrival

BLUE Small No Freeze-time

FRED Small Yes Arrival-departure

SFB Large No Freeze-time

CHOKe Small No Arrival

15744 Course Project 8

FRED• RED + Per-active-flow accounting

– protection of fragile flow

– penalizing non-responsive flow

– Flow type differentiation

• Key parameter: minq

– 2 or 4

• Weak point: – Compute avgq

per packet

New flow?

Calculate avg & maxq

Non-adaptive?

N

Y

minth<avg<maxth

Drop

N

Y

RobustRED

avg<minth Accept

N

Drop Tail

New state

Fragile

N

15744 Course Project 9

FRED performance

00.10.20.30.40.50.60.70.80.9

1

0.1 0.2 0.4 0.8 1 2 4 8UDP rate (Mbps)

UD

P T

hp

t (M

bp

s)

1 TCP,1 UDP

10 TCP, 1 UDP

10 TCP, 5 UDP

0

10

20

30

40

50

60

70

0.1 0.2 0.4 0.8 1 2 4 8UDP rate (Mbps)

UD

P Q

ueu

e S

ize

(pac

ket) 1 TCP,1 UDP

10 TCP, 1 UDP

10 TCP, 5 UDP

15744 Course Project 10

FRED characteristics

• Easy to configure, adaptive

• Buffer size requirement– Will degrade as DropTail with too many flows– “Two-packet-buffer” to keep fairness

0

0.25

0.5

0.75

1

10 20 40 45 50 60 70

Buffer size (#Packet)

Thr

ough

put (

Mbp

s)TCP_Thpt

UDP_thpt

15744 Course Project 11

CHOKe

Random

Same FlowID?

CHOose and Keep for responsive flows CHOose and Kill for unresponsive flows

>maxth?

minth

maxth

15744 Course Project 12

CHOKe

0

0.2

0.4

0.6

0.8

1

0.1 0.2 0.4 0.8 1 2 4 8

UDP rate (Mbps)

UD

P T

hro

ug

hp

ut

(Mb

ps)

1 TCP, 1 UDP 10 TCP, 1 UDP 10 TCP, 5 UDP

15744 Course Project 13

Parameters in CHOKe

0

0.05

0.1

0.15

0.2

0.25

1 2 5 10 15

Candidate Number

UD

P F

low

Th

rou

gh

pu

t (M

bp

s)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

2 1.6 1 0.8UDP rate (Mbps)

UD

PF

low

Th

rou

gh

pu

t (M

bp

s)

num = 1 num = 5num = 10 num = 15

15744 Course Project 14

BLUE •Main Point: Uses packet loss and link idle events instead of average queue length :

•Based on observation that RED is often forced into drop-tail mode

•Adapt to how bursty and persistent congestion is by looking at loss/idle events

15744 Course Project 15

BLUE AlgorithmPm is Blue’s packet dropping probability:

•Upon packet loss, if no update of pm in freeze_time then increase by d1

•Upon link idle, if no update of pm in freeze_time then decrease pm by d2

•d1 >> d2 •More critical to react quickly to increase in load

15744 Course Project 16

BLUE Characteristics

•More stable queue size and much better behavior with small buffers

•Good property damaged by non-responsive flows.

15744 Course Project 17

Stochastic Fair Blue(SFB)•Objective:

•Identify and penalize misbehaving flows

•Main Algorithm:

Create L hashes with N bins each

•Each bin keeps track of separate marking rate (pm)

•Rate is updated using standard technique(as BLUE)

•Flow uses minimum pm of all L bins it belongs to

•Non-misbehaving flows hopefully belong to at least one bin without a bad flow

15744 Course Project 18

SFB Characteristics

•Could effectively detect non-responsive flows and rate-limit them

•But not adaptive, the bandwidth share of non-responsive flows is controlled by a parameter(Boxtime) offered by the user.

•Boxtime is the time interval no packets from non-responsive flows can be enqueued.

15744 Course Project 19

SFB: Unfairness of Non-responsive Flows

Our solution: Randomized Boxtime a little bit.

15744 Course Project 20

Rate-limit Non-responsive flows

Time

UDP packets

Queue

Boxtime