aggressiveness protective fair queuing for bursty applications


Background: Network planning

Link Capacity

• Network Designers use the traffic properties to plan the capacity of the network.


Background: Exploiters

Link Capacity

• Exploiters– Malicious: Denial of Service (DDOS)– Innocent: pre-fetching, massive users

Drop

Exploiter


Background: Solution- Fair Scheduling protection against Exploiters

Link Capacity

• Weighted Fair Queuing (WFQ) mechanisms provides that the resource is fairly (typically equally) divided among all

Drop

Exploiter

Drop

1

1


Our main contribution

• The user traffic is bursty. • WFQ cannot provide fair service to bursty

applications in the presence of aggressive users

• We propose WFQ-like mechanism called Aggressiveness Protective Fair Queuing (APFQ) that solves this problem.


Bursty Application

• Many application are bursty (model on/off ~ active/idle)– Http

on off

Time

on off


Bursty Traffic

• Network Designers use the traffic burstiness property to plan the capacity of the network.

Link Capacity

Drop

Drop


Aggressive Users

• Aggressive user use the idle time to get more BW

Link Capacity

Drop

Drop


WFQ defensives

• WFQ cannot provide good fairness in the presence of such aggressive users.

Link Capacity

Drop

Drop


The effect of aggressive user on polite users (WFQ)

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

Link Capacity (Kb/s)

Perc

en

tag

e o

f P

ackets

tra

nsm

itte

d (

%)

All Polite - Polite traffic avarege

Mixed users - Polite traffic avarege

Mixed users - Aggressive trafficavarege


Aggressiveness Protective Fair Queuing (APFQ)

We propose a new WFQ-like mechanism called Aggressiveness Protective Fair Queuing (APFQ) that solves this problem by dynamically decreasing the weight of the aggressive users.


Agenda

• Related Work.

• Solution Requirements.

• APFQ algorithm.

• APFQ analysis

• Simulation.


Related Work• Dynamic WFQ was proposed to handle the fact that

it is hard to assign static weight accurately [Shin and el.

2001][Makrakis and el. 2001]. – Fix the weight according to arrival rate or the queue

length.

– Does not address bursty traffic problem.

• Dynamic WFQ was proposed as part of a mechanism to handle DDOS [Thomas and el. 2003]

– Penalty mechanism to flows

– Does not deal with traffic burstiness and does not suggest or analyze the weight function mechanism


Solution Requirements

• Provide fairness to polite users.

• The limitation imposed on the users is a function of the system load.– Protect innocent users by negatively discriminating

aggressive users on an overloaded Network.

Link Capacity

Drop

Drop


APFQ

• Dynamic weight function that reduces the weight assigned to aggressive users

• For every flow (user) the mechanism counts the amount of traffic that a source has generated in the near history

• It uses this amount to affect the weight given to the user.


Weight function

• BS – the assigned quota.• SM(t) – offered traffic during the last sliding.

window in time t.

• wo original fix weight.• α – punishment factor – configure by the system.

BStSM

BStSM

tSM

BSw

wtw

)(

)()

)(()(

0

0


APFQ Illustrated• Polite user transmit data:

• Aggressive User Transmitted data under WFQ

Time

• Aggressive User Transmitted data under APFQ


APFQ algorithm

Weight

71

W(0)

Time

Time

KBytes


Analysis pre conditions

• Polite user transmits at rate R for Ton and idle for Toff. • Aggressive user transmits at constant peak rate R.• N concurrently active users.• K aggressive users , N-K polite users.• For each user original fix weight wo = 1• Packets that are not transmitted within a period of ∆ from

their arrival time are dropped.• B is the output link capacity. • ∆ = Ton + Toff = sliding window size.• ƒ = burst factor =

TonTon

ToffTon


• Offered Data

• Transmitted Data WFQ

• Transmitted Data APFQ

Polite User

onWFQ

politeT

N

BD

onAPFQpoliteon T

KN

BDT

N

B

on

on

Tt

TtR

0)(tR


• Offered Data

•Total offered Data

• Transmitted Data WFQ

Naive Aggressive User

R

BSfR

N

BD

WFQ

naive

)(tR


•Transmitted Data APFQ

• For α =1

• For α=2

Naive Aggressive User

dtTT

N

BTon

ononAPFQ

naive

tD

1

Dt

APFQ

naiveTonon

ondtTT

KN

B

1

N

BfTD

APFQ

naive )log1(on

N

B

f

fTD

APFQ

naive

)

11(on


Continuous Naive Aggressive • Continuous Naive Aggressive - an aggressive user that was active in the previous window size.

• I.e., offered traffic during the last sliding

• Hence the assigned weight is fixed

fR

BStw

1)(

RtSM )(


Continuous Naive Aggressive

onAPFQ

naivecontT

KN

BfD

1 1

onAPFQ

naivecontT

N

BfD

1 1

•Transmitted Data APFQ

•For α =1 Exactly as polite use under APFQ

• For α=2 Exactly as polite use under APFQf

1


Sophisticated Aggressive

• Sophisticated Aggressive user is assumed to know the function used by APFQ and optimizes its offered traffic in order to maximize the traffic APFQ will transmit for him.

• An approach for the sophisticated aggressive user is to offer the same amount of traffic as the mechanism allow her to transmit.

•Sophisticated Aggressive user is assumed to know the function used by APFQ and optimizes its offered traffic in order to maximize the traffic APFQ will transmit for him.


Sophisticated User Upper Bound

• Lemma: Under APFQ a sophisticated aggressive user cannot transmit in a period of duration ∆ more than (m+2)·BS traffic where m is derived from equation

BSfDAPFQ

tedsophistica 212

1

BSfDAPFQ

tedsophistica 2133

2

11

f

m

i i


Sketch of proof

1

11 w

2

12 w

3

13 w

iwi

1

BSRi

tt ii

1

1

onii

Titt

1

on

m

ion TTi1


Sophisticated User Lower Bound

• Lemma: There is a strategy where the sophisticated aggressive user can transmit during an interval of length ∆ under APFQ with α at least (m+1)·BS traffic where m is derived from equation

.1

BSfDAPFQ

tedsophistica 112

2

BSfDAPFQ

tedsophistica 1133

111

fi

m

i


Optimal Strategy for sophisticated aggressive


Analysis Summery

User TypeWFQ transmitted traffic

APFQ transmitted traffic (α=1)

APFQ transmitted traffic (α=2)

Polite user111

Naïve aggressive userƒ1 + log ƒ2

Continuous naïve aggressive user

ƒ1

Sophisticated userƒ

f

1

212 f 2)1(33 f


Simulation

• Simulated APFQ on NS2

• NS2 code implementing WFQ contributed by Paulo Losi

• APFQ was implemented as a software wrapper around WFQ.


Tests Set-upWorkstation 1

Workstation 2

Workstation 3

Workstation N

Server

Router

.

.

.

.

200Kb

200Kb

200Kb

200Kb

Link Capacity


Experiment 1

• Examine the percentage of packets transmitted per flow as a function of the link capacity.

• Scenario 1: 12 polite users

• Scenario 2: 10 polite users and 2 aggressive users.


Experiment 1 Results

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

Link Capacity (Kb/s)

Perc

en

tag

e o

f P

ackets

tra

nsm

itte

d (

%)

All polite- WFQ Polite traffic avarege

Mixed users - WFQ Polite trafficavaregeMixed users- WFQ Aggressive trafficavaregeMixed users- APFQ Polite trafficavaregeMixed users- APFQ Aggressive trafficavarege


Experiment 2

• Examine how many aggressive users a given network can handle without negatively affecting the polite users.

• Test APFQ robustness to large networks.


Experiment 2

• 300 users with a variable number of aggressive users out of them.

• The number of aggressive users was increased in each round.

• The Link-capacity was set to 9000Kb/sec.


0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Number Of Aggressive Users

Pre

cen

tag

e o

f P

acke

ts t

ran

smit

ted

(%)

WFQ Polite traffic avarege

WFQ Aggressive traffic avarege

APFQ polite traffic avarege

APFQ Aggressive trafficavarege

Experiment 2 Results


Implementation consideration

• APFQ can use a regular WFQ.

• Experiments revealed that Dynamic WFQ, in some scenarios, can causes disorder.

• The cause of the problem is that the WFQ implementation implicitly assumed the weight of the queues is constant (i.e. static weight).


Conclusion

• Aggressive users use the idle time to get more bandwidth.

• WFQ has a fairness problems in the presence of aggressive users.

• APFQ is a mechanism that provide fairness in such cases, using a dynamic weight function.


Questions?

Thank You


Problem demonstration

1

0.25P4F=4

P3F=3

Time

P6F=9

8 7 6 5 4 3 2

1

1P3F=3

P2F=2

Time

P4F=4

6 6 5 4 3 2 1

1

1P2F=2

P1F=1

Time

P3F=3

6 5 4 3 2 1 0

P4F=4

P5F=5

P5F=5

P1F=1

P1F=1

P2F=2

V_t =0

V_t =1

V_t =2



1

0.25

p6F=9

Time

P8F=13

8 7 6 5 4 3 2

P7F=6

P1F=1

P2F=2

P3F=3

P5F=5

P4F=4

1

0.25

p6F=9

Time

P8F=13

8 7 6 5 4 3 2

P7F=6

P1F=1

P2F=2

P3F=3

P5F=5

P4F=4

1

0.25p6F=9

Time

P8F=13

8 7 6 5 4 3 2

P7F=6

P1F=1

P2F=2

P3F=3

P5F=5

P4F=4

V_t =9.2

V_t =10

V_t =8.4


1

0.25p6

F=9

Time

P8F=13

8 7 6 5 4 3 2

P5F=5

P1F=1

P2F=2

P3F=3

1

0.25p6

F=9

Time

P8F=13

8 7 6 5 4 3 2

P7F=6 P1

F=1P2

F=2P3

F=3

P4F=4

P4F=4

P5F=5

The new flow packet should have been transmitted by now

1

0.25p6F=9

Time

P8F=13

P7F=6

P5F=5

P1F=1

P2F=2

P3F=3

P4F=4

The new flow arrive and it’s finish time is set by the virtual time and not by the real round time (it finish time should have been 3)

V_t =7.6

V_t =6.8

V_t =6


P7F=6


Sketch of proof

1

11 w

2

12 w

3

13 w

iwi

1

aggressiveness protective fair queuing for bursty applications

Documents

fair service

user traffic

bwlink capacitydrop

bursty model onoff

traffic properties

presence of aggressive

traffic burstiness property

denial of service ddosinnocent