Providing Throughput
Differentiation for TCP Flows Using
Adaptive Two-Color Marking and
Two-Level AQM
Presented by
Vishal Misra
Columbia University in the city of New York
Joint work with
Y. Chait, C.V. Hollot, Don Towsley, H. Zhang (UMass-Amherst)
and John Lui (Chinese University of Hong Kong)
•Infocom 2002
Overview
• Background and motivation
• Fluid-flow model
– Two level PI
– Adaptive Rate Marker
• Simulations
• Conclusions
•Infocom 2002
Diffserv Architecture: Background
End-host:
- negotiates a profile with edgerouter
Edge router:
- per-flow traffic management
- marks packets as in-profile and outprofile
Core router:
- per class traffic management
- buffering and scheduling
based on marking at edge
•Infocom 2002
A,B
scheduling
marking
Leaky-bucket Marking at Edge
profile: pre-negotiated rate A, bucket size B
packet marking at edge based on per-flow profile
Rate A
B
User packets
•Infocom 2002
Assured Forwarding at Core
• active queue management
– computes average queue length, x
– p1: drop prob. of green packet
– p2: drop prob. of red packet
Drop prob
1
•Infocom 2002
Avg. Queue length
TCP over AF Service
Profile:A,B
marker
bottleneck core
TCP
Other flows
• Question: is it possible to provide a TCP flow a fixed (minimum)
rate through proper choice of parameters (A,B)
• Studied in
“Achievable Service Differentiation with Token Bucket marking for TCP”
[Sahu et al. Sigmetrics 2000]
•Infocom 2002
Ideal Differentiation Not Possible
• consider two identical TCP
flows (f1, f2)
• conventional service
– same achieved rate for both flows
• assured forwarding
– ideally want to have achieved
rate, r, proportional to assured
rate A, i.e,
r1/r2 = A1/A2
• not possible with token
parameter setting
Profile-based marking favors flows with lower token-bucket rate A
•Infocom 2002
Proposed Solution
• Make bucket rate adaptive
– A -> A(t)
• Design controller to set A(t) at the edge
• Implement two-level PI at core
•Infocom 2002
TCP - Fluid Flow Model
[MGT Sigcomm 2000]
• Window size
dWi
1 Wi Wi (t  Ri )


p (t  Ri )
dt
Ri
2 Ri (t  Ri )
add
increase
• Queue length
Wi
dq
  Ni  C ,
dt
i Ri
incoming
traffic
• Round trip
•Infocom 2002
mult
decrease
outgoing
traffic
q
Ri  Ti
C propagation
queuing delay
delay
loss
arrival rate
q  [0, qmax ]
Fluid Flow Model: Adding DiffServ
Ai , bi
• Token bucket per aggregate:
 1
Fraction of fluid
marked green
• Two-color marking
• Loss probability
•Infocom 2002
f i  min {1, Ai }
g
ri
 i
i
f

1

f
 r
g
pi  f pg  (1 - f ) pr
i
g
i
g
2-level PI Controller at Core
green packets
q g
ref
•Use single controller
•Define two desired queue
g
r
lengths qref
and qref
•PI regulates buffer queue to qref
•For over-provisioned, queue
r
converges to qref, for underprovisioned queue converges
g
to qref
differenti ating 
controller
pg
AQMg
queue
 ri
p g 


 pr 
q
1
f
s  q

q r
ref
AQM r
pr
red packets
controller
•Infocom 2002
Adaptive Rate Marker at Edge
•ARM: Another PI controller
•Input signal: (estimate of)
Aggregation
TCP Window
achieved throughput
1
s
•Output signal: Bucket rate A
Wi
g
W
r
N
R
F(s)
g
A
A

ARM
Bucket Rate Controller
•Infocom 2002
Sending Rate
Estimation
~
r
Linearized Fluid Model
e  sR1
~
r1
ARM 1
A1

g1
A1
F(s)
 g1 
 p g 
 g 
 1
 p r 
g
s  W1
1

W1

 g m 
 p g 
 g 
 m
 pr 
N1
R1

r1
congested

Wm
1
g
s  Wm
m
s
rm
Nm
Rm
Am
ARM m
e  sRm
q
qrefr

~
rm
p g 


 pr 
f
q

F(s)
AQMg
queue
1
g m
Am
•Infocom 2002
p g
qrefg
1
AQM r
pr
ns-2Simulation topology
marking
edges
sources
N1 flows
T p1 msec
s1
receivers
1
15 msec differenti ating
queue
N 2 flows s 2
N 3 flows s3
•Infocom 2002
T p2 msec
15 msec
25 msec
2
T p3 msec
3
15 msec
3750 packet /sec

ns Simulations
2500
r~1  2000 pkt/sec
r~2  500 pkt/sec
r~  1250 pkt/sec
3
1500
ARM
2000
1000
token bucket
token bucket
1500
500
ARM
1000
edge 1
500
0
100
200
edge 2
300
0
0
100
200
300
Smooth curve : fluid model
2000
800
differentiating queue
600
token bucket
1500
400
token bucket
ARM
1000
200
edge 3
500
•Infocom 2002
0
100
200
300
0
0
100
200
300
400
ns Simulations
2500
• Added transient FTP flows
• Added HTTP flows
2000
edge 1
1500
edge 3
1000
edge 2
500
0
•Infocom 2002
0
50
100
150
200
250
300
350
400
ns Simulations
2500
• Added transient FTP flows
• Added HTTP flows
2000
•• Increase capacity by 20%
edge 1
edge 3
1500
1000
edge 2
500
0
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0
50
100
150
200
250
300
350
400
ns Simulations
• Added another edge w/o
SLA
2500
1000
2000
800
1500
600
1000
400
500
200
edge 1
0
0
200
400
edge 2
600
800
2000
0
0
200
400
600
800
600
800
1500
edge 4
1500
1000
1000
500
500
edge 3
0
•Infocom 2002
0
200
400
600
800
0
0
200
400
ns Simulations
2500
2000
• Added another edge w/o 2000
1500
SLA
•Increase capacity by 20% 1000
1500
1000
500
500
edge 2
egde 1
0
0
100
200
300
400
2500
0
0
100
200
300
400
300
400
2000
edge 4
2000
1500
1500
1000
1000
500
500
edge 3
0
•Infocom 2002
0
100
200
300
400
0
0
100
200
ns Simulations
2500
• Decrease capacity by 20%
2000
edge 1
1500
edge 3
1000
edge 2
500
0
•Infocom 2002
0
50
100
150
200
250
300
350
400
Conclusions and Future Work
• A modification to the DiffServ architecture proposed
• Control theoretic design and stability analysis of
system performed
• SLA-consistent throughput differentiation
simulations
• Investigate proportional (or fair) allocation of excess
bandwidth
• Improve model to account for small bucket size
•Infocom 2002