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Aggressiveness Protective Fair Queuing for Bursty Applications. Nir Halachmi (IDC) Joint work with Dr. Anat Bremler Barr (IDC) and Prof. Hanoch Levy (TAU). Background: Network planning. Network Designers use the traffic properties to plan the capacity of the network. Link Capacity. - PowerPoint PPT Presentation
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APFQ - Nir Halachmi (IDC)
Aggressiveness Protective Fair Queuing for Bursty Applications
Nir Halachmi (IDC)
Joint work with
Dr. Anat Bremler Barr (IDC) and Prof. Hanoch Levy (TAU)
APFQ - Nir Halachmi (IDC)
Background: Network planning
Link Capacity
• Network Designers use the traffic properties to plan the capacity of the network.
APFQ - Nir Halachmi (IDC)
Background: Exploiters
Link Capacity
• Exploiters– Malicious: Denial of Service (DDOS)– Innocent: pre-fetching, massive users
Drop
Exploiter
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
Bursty Application
• Many application are bursty (model on/off ~ active/idle)– Http
on off
Time
on off
APFQ - Nir Halachmi (IDC)
Bursty Traffic
• Network Designers use the traffic burstiness property to plan the capacity of the network.
Link Capacity
Drop
Drop
APFQ - Nir Halachmi (IDC)
Aggressive Users
• Aggressive user use the idle time to get more BW
Link Capacity
Drop
Drop
APFQ - Nir Halachmi (IDC)
WFQ defensives
• WFQ cannot provide good fairness in the presence of such aggressive users.
Link Capacity
Drop
Drop
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
Agenda
• Related Work.
• Solution Requirements.
• APFQ algorithm.
• APFQ analysis
• Simulation.
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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 - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
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 - Nir Halachmi (IDC)
APFQ Illustrated• Polite user transmit data:
• Aggressive User Transmitted data under WFQ
Time
• Aggressive User Transmitted data under APFQ
APFQ - Nir Halachmi (IDC)
APFQ algorithm
Weight
71
W(0)
Time
Time
KBytes
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
• 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
APFQ - Nir Halachmi (IDC)
• Offered Data
•Total offered Data
• Transmitted Data WFQ
Naive Aggressive User
R
BSfR
N
BD
WFQ
naive
)(tR
APFQ - Nir Halachmi (IDC)
•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
APFQ - Nir Halachmi (IDC)
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 )(
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
Optimal Strategy for sophisticated aggressive
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
Simulation
• Simulated APFQ on NS2
• NS2 code implementing WFQ contributed by Paulo Losi
• APFQ was implemented as a software wrapper around WFQ.
APFQ - Nir Halachmi (IDC)
Tests Set-upWorkstation 1
Workstation 2
Workstation 3
Workstation N
Server
Router
.
.
.
.
200Kb
200Kb
200Kb
200Kb
Link Capacity
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
Experiment 2
• Examine how many aggressive users a given network can handle without negatively affecting the polite users.
• Test APFQ robustness to large networks.
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
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).
APFQ - Nir Halachmi (IDC)
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.
APFQ - Nir Halachmi (IDC)
Questions?
Thank You
APFQ - Nir Halachmi (IDC)
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
APFQ - Nir Halachmi (IDC)
Problem demonstration
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
APFQ - Nir Halachmi (IDC)
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
Problem demonstration
P7F=6
APFQ - Nir Halachmi (IDC)
Sketch of proof
1
11 w
2
12 w
3
13 w
iwi
1