evaluation of queue management algorithms
DESCRIPTION
Evaluation of Queue Management Algorithms. Ningning Hu, Liu Ren, Jichuan Chang 30 April 2001. Motivation. Typical queuing discipline: DropTail Active queue management: RED (93’), BLUE (99’), … FRED (97’), SFB (99’), CHOKe (2000’) Problem: How to compare them? - PowerPoint PPT PresentationTRANSCRIPT
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15744 Course Project 1
Evaluation of Queue Evaluation of Queue Management AlgorithmsManagement Algorithms
Ningning Hu, Liu Ren, Jichuan Chang
30 April 2001
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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
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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
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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
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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
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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)
DropTailREDFREDBLUESFBCHOKe
Figure 1. UDP Thpt (Mbps)
Figure 2. UDP Queue Size (packet)
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15744 Course Project 7
ConclusionAlgorithm Link
Utilization Fairness Ease 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
ComputationalOverhead
RED Large No Arrival
BLUE Small No Freeze-time
FRED Small Yes Arrival-departure
SFB Large No Freeze-time
CHOKe Small No Arrival
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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
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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 Th
pt (M
bps)
1 TCP,1 UDP10 TCP, 1 UDP10 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
ueue
Siz
e (p
acke
t) 1 TCP,1 UDP10 TCP, 1 UDP10 TCP, 5 UDP
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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 70Buffer size (#Packet)
Thro
ughp
ut (M
bps)
TCP_ThptUDP_thpt
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15744 Course Project 11
CHOKe
Random
Same FlowID?
CHOose and Keep for responsive flows CHOose and Kill for unresponsive flows
>maxth?minth
maxth
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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 Th
roug
hput
(Mbp
s)
1 TCP, 1 UDP 10 TCP, 1 UDP 10 TCP, 5 UDP
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15744 Course Project 13
Parameters in CHOKe
0
0.05
0.1
0.15
0.2
0.25
1 2 5 10 15Candidate Number
UD
P Fl
ow T
hrou
ghpu
t (M
bps)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2 1.6 1 0.8UDP rate (Mbps)
UD
PFlo
wTh
roug
hput
(M
bps)
num = 1 num = 5num = 10 num = 15
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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
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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
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15744 Course Project 16
BLUE Characteristics
•More stable queue size and much better behavior with small buffers
•Good property damaged by non-responsive flows.
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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
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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.
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15744 Course Project 19
SFB: Unfairness of Non-responsive Flows
Our solution: Randomized Boxtime a little bit.
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15744 Course Project 20
Rate-limit Non-responsive flows
Time
UDP packets
Queue
Boxtime