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![Page 1: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/1.jpg)
Flow and Congestion Control for Reliable Multicast Communication
In Wide-Area Networks
Supratik Bhattacharyya
Department of Computer Science
University of Massachusetts Amherst
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Talk Overview
General Problem
Single-rate source-based congestion control (CC) :
the Loss Path Multiplicity problem
a scalable and “fair” congestion control approach
a prototype implementation for active networks
Multi-rate flow-controlled bulk data transfer
Future Research Ideas
![Page 3: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/3.jpg)
Flow/Congestion Control in Wide-Area Networks
Congestion Control short term : adapt
transmission rate to changing traffic conditions.
Flow Control : longer term : tailor rate
to available capacity
End-to-end approach suitable for today’s networks
Internet
Data
Data
Source
Receiver
Feedback
Feedback
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Multicasting
My focus : one-to-many reliable multicasting
Network nodes replicate data packets
Network bandwidth used efficiently
Source
R1
R2R3
R4
Router
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Multicast Flow/Congestion Control : a hard problem
Challenges - many rcvrs, many network paths :
Heterogeneity
– links, receiver capabilities
Scale– feedback implosion
Fairness – how to share bandwidth
with unicast: end-to-end feedback
Source
R1 R4R3R2
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Talk Overview
General Problem
Single-rate source-based congestion control (CC) :
the Loss Path Multiplicity problem
a scalable and “fair” congestion control approach
a prototype implementation for active networks
Multi-rate flow-controlled bulk data transfer
Future Research Ideas
![Page 7: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/7.jpg)
Feedback Aggregation
Challenge : How to aggregate feedback into single rate control decision
loss indications (LI)
filterfilter Rate controlRate control
algorithmalgorithm
congestion signal (CS)
rate change
Congestion signals (CS): filtered versions of loss indications (LI) : congestion signal probability filters can be distributed
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Problem : Loss Path Multiplicity (LPM)
Copies of same packet lost on many network paths
Set of receivers treated as single aggregate receiver
Example :
N : no. of receivers
p : loss prob. on link to each rcvr.
: congestion signal probability
) 1 (1 p N
R2
?
R1 R3
LI LI
1 as N
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How Severe is the LPM Problem?
Severe degradation in throughput with -
no. of receivers independent losses
0
2
4
6
8
10
12
0 50 100150200 250300350400450 500
No. of Receivers
f=0.1
f=0.5
f=0.9
p=0.05
Example :
p
f : fraction of end-to-end loss on independent link
. . .
fpend-to-end loss prob. =
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Feedback Aggregation/Filtering :Related Work
Restrict response to one LI per time interval T Montgomery 1997
Restrict response to subset of receivers :
choose K receivers out of N as representatives
Delucia et al. 1997
Reduce response to each LI :
Golestani, Bhattacharyya 1998, Delucia et al. 1997
Q : How much bandwidth should a multicast session get?
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Background : “Fair” Bandwidth Sharing
Challenge : How to achieve “fair” sharing among multicast and unicast sessions
Multicast allocation according to “worst” end-to-end path
Multicast session shares equally with a unicast session on its “worst” end-to-end path.
L1 - 1 Mbps, L2 - 2 Mbps
Ucast1
L2
L1
Mcast
Mbpsr 5.0 1Ucast
Mbpsr 5.0 Mcast
Mbpsr 5.1 Ucast2
Ucast2
L2
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Background : End-to-end Rate Control Algorithms
: rate after i-th update
Additive increase, multiplicative decrease :
on congestion signal :
else, per T :
We derive average session throughput B
1 1 rr ii
)11( 1 Crr ii
ri
, ,TCCTB
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Solution to LPM Problem : Our Approach
Identify (estimate) “worst” receiver
Respond to LIs from only “worst” receiver
prevents throttling of multicast transmission rate
allows fair bandwidth sharing
Bhattacharyya, Towsley, Kurose. Infocom ‘99
. . .
Modified Star
0
2
4
6
8
10
12
14
16
0 5 10 15 20 25 30 35 40 45 50
No. of Representatives (K)
representativeapproach
worst rcvr. approach
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Simulation of LPM Solution
Simulation Settings: 5 multicasts over L1, L2, each
tracks L1 A : 5 unicasts over L1, 5 over L2 B : 5 more unicasts on L1 C : same as B, each multicast
tracks L2 instead
Example topology :
L1 L2
L1, L2 : 300 pkts/sec
Sources
Rcvrs
mcast ucastover L1
ucastover L2
Simulation Settings
A
B
C
29.8 30.2 30.3
Throughput (pkts/sec)
20.9
30.0
20.9 39.9
17.1 30.5
Rcvrs
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Realizing the Worst Receiver Approach
Use end-to-end loss probability estimates :
N rcvrs - rcvr i reports Xi losses out of S pkts
choose rcvr with highest no. of losses
Worst Estimate-based Tracking (WET)
WET is sensitive to S : large S good estimate small S likely to choose wrong receiver as worst
Q : What can we do for small S ?
Challenge : How to identify the worst receiver?
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Current Work : Robust Congestion Control
Our Idea : On LI from receiver i, reduce rate with probability
Linear Proportional Response (LPR) :
Observation : small S : LPR more robust
S : LPR allocates more than fair share to multicast session !
Example : 2 receivers, loss prob. 0.05 and 0.10
13
14
15
16
17
18
19
20
21
0 50 100 150 200 250 300 350 400 450 500
No. of observations (S)
LPR
WETFair Share
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Ongoing Work
Related : Random Listening Algorithm (RLA) [Wang98]
Result : Our approach (LPR) provides tighter upper bound on r
LPR :
RLA : Nr
4 Nr 0
1
2
3
4
5
6
0 5 10 15 20 25 30
No. of receivers (N)
RLA
LPR
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A Prototype of Worst Receiver Approach for Active Networks
“Worst” receiver has largest value of
Active Servers : aggregate feedback
help in identifying “worst” receiver
p : loss prob. estimateRTT : round trip time estimate
Source
R1 R2 R3 R4
AS1 AS2
Our Rate Control Algorithm
pRTTv
v1 v2v3 v4
v1 v4
Worst : R1
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Talk Overview
General Problem
Single-rate source-based congestion control (CC) :
the Loss Path Multiplicity problem
a scalable and “fair” congestion control approach
a prototype implementation for active networks
Multi-rate flow-controlled bulk data transfer
Future Research Ideas
![Page 20: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/20.jpg)
Flow-controlled Bulk Data Transfer : Overview
Challenge : reliable delivery of finite volume
of data diverse receive-rates
Goal : minimize average completion
time
Approach : multiple IP multicast groups
(channels)
R1=1 R2=2 R3=3
Bhattacharyya, Kurose, Towsley, Nagarajan. Infocom ‘98
R4=4
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Flow-controlled Bulk Data Transfer
2 pkts/sec4 pkts/sec
1 pkt/sec
a
b
c
d
b dr1 = 1
r2 = 1
r3 = 2 c d
R1R2
R4
a
a
a
b
b
cd
R1,R2,R4
R2,R4
R4
Q : How to : assign channel rates? assign receivers to channels? partition data among
channels?
Assumptions : error-free channels known, static receive-rate
constraints
Solution with unlimited channels :
minimizes average completion time
minimizes bandwidth
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Flow-controlled Bulk Data Transfer
2 pkts/sec4 pkts/sec
1 pkt/sec
a
b
c
d
b dr1 = 1
r2 = 1
r3 = 2 c d
R1
R2R4
a
a
a
b
b
cd
R1,R2,R4
R2,R4
R4
Q : How to : assign channel rates? assign receivers to channels? partition data among
channels?
Assumptions : error-free channels known, static receive-rate
constraints
Solution with unlimited channels :
minimizes average completion time
minimizes bandwidth
c
cd
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Flow-controlled Bulk Data Transfer
2 pkts/sec4 pkts/sec
1 pkt/sec
a
b
c
d
b dr1 = 1
r2 = 1
r3 = 2 c d
R1
R2R4
a
a
a
b
b
cd
R1,R2,R4
R2,R4
R4
Q : How to : assign channel rates? assign receivers to channels? partition data among
channels?
Assumptions : error-free channels known, static receive-rate
constraints
Solution with unlimited channels :
minimizes average completion time
minimizes bandwidth
c
cd
d
b
![Page 24: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/24.jpg)
Limited Number of Channels
Static rate assignment :
Q : Given K channels and N (>K) receive rates, which K rates to match?
Approach : minimize average completion time
dynamic programming solution - O(N3 K)
Dynamic rate assignment : reassign rates when faster receivers finish optimization problem too hard Our approach : Simple heuristics
![Page 25: Flow and Congestion Control for Reliable Multicast Communication In Wide-Area Networks Supratik Bhattacharyya Department of Computer Science University.](https://reader035.fdocuments.net/reader035/viewer/2022070413/5697bf9d1a28abf838c93fa0/html5/thumbnails/25.jpg)
Heuristics for Channel Rate Assignment
Fastest Receivers First (FRF)
Slowest Receivers First (SRF)
Equal Partitions (EQ) distribute rates “smoothly” over entire
range of receive rates
Maximize Utilized Capacity (MUC) :
allocate channel rate to maximize sum of rates at which unfinished receivers receive
dynamic programming solution
no. of receivers
receive rates
Example :
Choose rates for 3 channels
EQ:
MUC:
G1G2
G3
G4
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Summary of Results
Average Completion time scales well :
200
1000
1500
0 100 200 300 400
No. of Receivers (X)
SRF
STATIC
MUC
IDEAL
Small no. of channels reqd :
200
1000
2600
0 2 4 6 8 10 12 14 16
Number of Channels (K)
SRF
STATICMUC
IDEAL
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Summary of Contributions
Single-rate source-oriented multicast CC : identified and studied Loss Path Multiplicity
problem proposed a scalable and “fair” congestion control
approach current work : robust congestion control schemes developing a prototype implementation for active
networks
Developed efficient algorithms for flow-controlled multicast of bulk data 1
1 : U.S. patent pending
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Other Interesting Projects
RMTP : A Reliable Multicast Transport Protocol 1
A Class of End-to-end Congestion Control Algorithm for the Internet 2
Design and Implementation an Adaptive Data Link Layer Protocol for an ATM Wireless LAN
2 : Golestani and Bhattacharyya. ICNP ‘98
1 : Paul, Sabnani, Lin, Bhattacharyya. JSAC 97
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Future Research Ideas
Immediate : prototype CC protocol for
active networks robust multicast CC
schemes
Short Term : multicast CC for continuous
media CC with enhanced network
support
Looking ahead :
network measurements support for adaptive
applications active services differentiated services
Open to new ideas and collaborations !