Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering...
38
Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering University of Delaware May 19th / 2004 Rafael Nunez [email protected] Gonzalo Arce [email protected]
-
date post
20-Dec-2015 -
Category
Documents
-
view
214 -
download
0
Transcript of Diffusion Mechanisms for Active Queue Management Department of Electrical and Computer Engineering...
Diffusion Mechanisms for Active Queue Management
Department of Electrical and Computer EngineeringUniversity of Delaware
May 19th / 2004
Rafael Nunez
Gonzalo Arce
2
Diffusion Mechanisms for Active Queue Management
Introduction Diffusion Early Marking Performance Conclusions and Future Work
3
The Internet Today
4
Congestion
Desirable control: distributed, simple, stable and fair.
5
Problems with Tail Dropping
Penalizes bursty traffic
Discriminates against large propagation delay connections.
Global synchronization.0 2 4 6 8 10 12 14 16 18 20
0
10
20
30
40
50
60
70
80
90
100Instantaneous Queue Size - Drop Tail
Time (seconds)
Que
ue (
Pac
kets
)
6
Active Queue Management (AQM)
Random Early Detection (Floyd and Jacobson, 1993)
Router becomes active in congestion control.
RED has been deployed in some Cisco routers.
7
Random Early Detection (RED)
Random packet drops in queue. Drop probability based on average queue:
q n6@
= 1- wq
_ i$q n - 1
6 @+wq$q n
6@
Four parameters: qmin qmax Pmax wq
(overparameterized)
8
Queue Behavior in RED
0 2 4 6 8 10 12 14 16 18 200
10
20
30
40
50
60
70
80
90
100Queue Behavior in RED
Time (seconds)Q
ueue
(P
acke
ts)
Instantaneous QueueAverage Queue
0 2 4 6 8 10 12 14 16 18 200
10
20
30
40
50
60
70
80
90
100Queue Behavior in Drop Tail
Time (seconds)
Que
ue (
Pac
kets
)
9
Queue Behavior in RED (2)
20 new flows every 20 seconds
Wq = 0.01 Wq = 0.001
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80Queue Behavior in RED
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100Queue Behavior in RED
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
10
Other AQM’s Schemes
Adaptive RED, REM, GREEN, BLUE,… Problems:
Over-parameterization Not easy to implement in routers Not much better performance than drop
tail
11
Diffusion Mechanisms for Active Queue Management
Introduction Diffusion Early Marking Performance Conclusions and Future Work
√
12
Diffusion Mechanisms for AQM
Instantaneous queue size. Better packet marking strategy. Simplified parameters.
13
Probability of Marking a Packet
Gentle RED function closely follows:
P [n] / P (qn) = Sqncma
(A)
14
Evolution of the Congestion Window
TCP in steady state:
PacketsBetweenDrops= 83W2
p1 = 8
3W2
(B)
15
Traffic in the Network
Congestion Window = Packets In The Pipe + Packets In The Queue
Or:
43W $N= MSS
B $RTT +qd(C)
From (A), (B), (C), and knowing that: RTT=D+q$ BMSS
P (q) = Sqcma
$N2
a=Log S
qd; ELog 2
3: D- 2 $Log MSS
B $D +2 $qd; D
where
16
Probability Function
P (q) = Sqcma
$N2, if q>S$N2̂h1/a
1 , otherwise
*
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1P(Q/S, N)
Q/S
P(Q
/S,
N)
N = 1N = 5N = 10
17
Error Diffusion
Packet marking is analogous to halftoning: Convert a continuous gray-scale image into black
or white dots Packet marking reduces to quantization
Error diffusion: The error between input (continuous) and output (discrete) is incorporated in subsequent outputs.
18
Diffusion Mechanism
19
Diffusion Mechanism
20
Diffusion Mechanism
21
Diffusion Mechanism
22
Diffusion Mechanism
23
Diffusion Mechanism
24
Diffusion Mechanism
25
Diffusion Mechanism
26
Diffusion Mechanism
27
Diffusion Mechanism
28
Diffusion Mechanism
29
Diffusion Mechanism
30
Algorithm Summary
D[n] =1, if (P [n] - P
e[n]) H 2P [n]0, otherwise
)
P (q) = Sqcma
$(N $Ef)2, if q>S$(N $Ef)2_ i1/a
1 , otherwise
*
a=Ln S
qd; ELn 2
3: D- 2 $Ln MSS
B $D +2 $qd; D
• Diffusion Early Marking decides whether to mark a packet or not as:
Where:
Pe[n]= bi$De[n - i]
i= 1
M
!
De[n] =(P [n] +Pe[n]) - D[n]
M=2, b1=2/3, b2=1/3
Remember:
31
Diffusion Mechanisms for Active Queue Management
Introduction Diffusion Early Marking Performance Conclusions and Future Work
√
√
32
Dropping Packets
0 10 20 30 40 50 60 70 80 90 1000
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2Diffusion Early Marking: Drops vs. Time (1 Flow)
Time (seconds)
Dro
ps (
pack
ets)
0 10 20 30 40 50 60 70 80 90 1000
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2RED: Drops vs. Time (1 Flow)
Time (seconds)
Dro
ps (
pack
ets)
33
Window Size
0 5 10 15 20 25 30 35 40 45 500
10
20
30
40
50
60
70
80
90
100RED: Congestion Window Size vs. Time (2 Flows)
Time (seconds)
Con
gest
ion
win
dow
siz
e (p
acke
ts)
Congestion Window 1Congestion Window 2Average Congestion Window 1Average Congestion Window 2
2 Flows:
10 Flows
0 1 2 3 4 5 6 7 8 9 10 110
2
4
6
8
10
12
14
16
18
20Diffusion Early Marking: Average Congestion Window Size vs. Time (10 Flows)
Flow ID
Ave
rage
Con
gest
ion
win
dow
siz
e (p
acke
ts)
0 1 2 3 4 5 6 7 8 9 10 110
2
4
6
8
10
12
14
16
18
20RED: Average Congestion Window Size vs. Time (10 Flows)
Flow ID
Ave
rage
Con
gest
ion
win
dow
siz
e (p
acke
ts)
0 5 10 15 20 25 30 35 40 45 500
10
20
30
40
50
60
70
80
90
100Diffusion Early Marking: Congestion Window Size vs. Time (2 Flows)
Time (seconds)
Con
gest
ion
win
dow
siz
e (p
acke
ts)
Congestion Window 1Congestion Window 2Average Congestion Window 1Average Congestion Window 2
34
Stability of the Queue
100 long lived connections (TCP/Reno, FTP) Desired queue size = 30 packets
0 2 4 6 8 10 12 14 16 18 200
10
20
30
40
50
60
70
80
90
100Queue Behavior in RED
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
0 2 4 6 8 10 12 14 16 18 200
10
20
30
40
50
60
70
80
90
100Diffusion Early Marking Queue
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
35
Changing the number of flows
20 new flows every 20 seconds
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100Queue Behavior in RED
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100Diffusion Early Marking Queue
Time (seconds)
Que
ue (
Pac
kets
)
Instantaneous QueueAverage Queue
36
Diffusion Mechanisms for Active Queue Management
Introduction Diffusion Early Marking Performance Conclusions and Future Work
√
√
√
37
Conclusions and Future Work
Queue length stabilized and controlled without adjusting parameters.
Diffusion mechanism improves the behavior of the proposed AQM scheme.
Future Work: Estimation of parameters Analyze more traffic scenarios Compare with other AQMs Use diffusion mechanism in other AQMs
38
Diffusion Mechanisms for Active Queue Management
Introduction Diffusion Early Marking Parameter Estimation Conclusions and Future Work
√
√
√
√
