fast tcp steven low cs/ee netlab.caltech.edu oct 2003
TRANSCRIPT
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FAST TCP
Steven Low
CS/EEnetlab.CALTECH.edu
Oct 2003
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FAST Protocols for Ultrascale Networks
netlab.caltech.edu/FAST
Internet: distributed feedback control system TCP: adapts sending rate to congestion AQM: feeds back congestion information
Rf (s)
Rb’(s)
x
))((1
lll
l ctyc
p
)()(1)( tan)(
)()(1-2
tqtttT
wx iid
tqtxi
ii ii
ii
y
pq
TCP AQM
Theory
Calren2/Abilene
Chicago
Amsterdam
CERN
Geneva
SURFNet
StarLight
WAN in LabCaltech
research & production networks
Multi-Gbps50-200ms delay
Experiment
Students Choe (Postech/CIT) Hu (Williams) J. Wang (CDS) Z.Wang (UCLA) Wei (CS)
Industry Doraiswami (Cisco) Yip (Cisco)
Faculty Doyle (CDS,EE,BE) Low (CS,EE) Newman (Physics) Paganini (UCLA)
Staff/Postdoc Bunn (CACR) Jin (CS) Ravot (Physics) Singh (CACR)
Partners CERN, Internet2, CENIC, StarLight/UI, SLAC, AMPATH, Cisco
People
155Mb/s
slowstart
equilibrium
FASTrecovery
FASTretransmit
timeout
10Gb/s
Implementation
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netlab.caltech.edu
Outline
Motivation Network model FAST TCP
Equilibrium Stability Experiments
TCP/IP
Applications
TCP/AQM
IP
Transmission
WWW, Email, Napster, FTP, …
Ethernet, ATM, POS, WDM, …
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High Energy Physics Large global collaborations
2000 physicists from 150 institutions in >30 countries 300-400 physicists in US from >30 universities & labs
SLAC has 500TB data by 4/2002, world’s largest database Typical file transfer ~1 TB
At 622Mbps: ~ 4 hrs At 2.5Gbps: ~ 1 hr At 10Gbps: ~15min Gigantic elephants!
LHC (Large Hadron Collider) at CERN, to open 2007 Generate data at PB (1015B)/sec Filtered in realtime by a factor of 106 to 107
Data stored at CERN at 100MB/sec Many PB of data per year To rise to Exabytes (1018B) in a decade
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HEP high speed network
… that must change
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HEP Network (DataTAG)
NLNLSURFnet
GENEVA
UKUKSuperJANET4ABILEN
E
ABILENE
ESNETESNET
CALREN
CALREN
ItItGARR-B
GEANT
NewYork
FrFrRenater
STAR-TAP
STARLIGHT
Wave
Triangle
2.5 Gbps Wavelength Triangle 2002 10 Gbps Triangle in 2003
Newman (Caltech)
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Performance at large windowsns-2 simulation
10Gbps
capacity = 155Mbps, 622Mbps, 2.5Gbps, 5Gbps, 10Gbps; 100 ms round trip latency; 100 flowsJ. Wang (Caltech, June 02)
27%
txq=100 txq=10000
95%1G
Linux TCP Linux TCP FAST
19%
average utilization
capacity = 1Gbps; 180 ms round trip latency;1 flowC. Jin, D. Wei, S. Ravot, etc (Caltech, Nov 02)
DataTAG Network:CERN (Geneva) – StarLight (Chicago) – SLAC/Level3 (Sunnyvale)
txq=100
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Outline
Motivation Network model FAST TCP
Equilibrium Stability Experiments
TCP/IP
Applications
TCP/AQM
IP
Transmission
WWW, Email, Napster, FTP, …
Ethernet, ATM, POS, WDM, …
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netlab.caltech.edu
Congestion Control
~ W packets per RTT Lost packet detected by missing ACK Congestion signal: delay and loss
RTT
time
time
Source
Destination
1 2 W
1 2 W
1 2 W
data ACKs
1 2 W
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Congestion control
xi(t)
pl(t)
Example congestion measure pl(t) Loss (Reno) Queueing delay (Vegas)
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netlab.caltech.edu
TCP/AQM
Congestion control is a distributed asynchronous algorithm to share bandwidth
It has two components TCP: adapts sending rate (window) to congestion AQM: adjusts & feeds back congestion information
They form a distributed feedback control system Equilibrium & stability depends on both TCP and AQM And on delay, capacity, routing, #connections
pl(t)
xi(t)TCP: Reno Vegas
AQM: DropTail RED REM/PI AVQ
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netlab.caltech.edu
Network model
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
lieR lis
lif link uses source if
lieR lislib link uses source if R
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for every RTT
{ if W/RTTmin – W/RTT < then W ++
if W/RTTmin – W/RTT > then W -- }
queue size
Vegas model
iiiii
i dtqtxtT
x )()( if )(
12
else 0ix
Fi:
iiiii
i dtqtxtT
x )()( if )(
12
Gl:))((1
llcl ctypl
Link queueing delay
E2E queueing delay
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Vegas model
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
1)(
l
ll c
tyG
ii
ii
dtqtx
i tTF
)()(
21sgn
)(
1
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Outline
Motivation Network model FAST TCP
Equilibrium Stability Experiments
TCP/IP
Applications
TCP/AQM
IP
Transmission
WWW, Email, Napster, FTP, …
Ethernet, ATM, POS, WDM, …
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netlab.caltech.edu
Methodology
Protocol (Reno, Vegas, RED, REM/PI…)
Equilibrium Performance
Throughput, loss, delay
Fairness Utility
Dynamics Local stability Cost of stabilization
))( ),(( )1(
))( ),(( )1(
txtpGtp
txtpFtx
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Model
c1 c2
Network Links l of capacities cl
Sources sL(s) - links used by source sUs(xs) - utility if source rate = xs
x1
x2
x3
121 cxx 231 cxx
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Summary: duality model
cRx
xUs
ssxs
subject to
)( max0
Flow control problem (Kelly, Malloo, Tan 98)
TCP/AQM Maximize utility with different utility functions
Primal-dual algorithm
))( ),(( )1(
))( ),(( )1(
tRxtpGtp
txtpRFtx T
Reno,
VegasDropTail, RED, REM
Result (L 00): (x*,p*) primal-dual optimal iff 0 ifequality with ** lll pcy
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Example utility functions
1 log
1 )1( :General
log : Vegas
32log
1 :2-Reno
3/2tan23
:1-Reno
11
1
i
i
ii
ii
ii
i
iii
x
x
x
Tx
Tx
T
TxT
/
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Game interpretation
lllssss
xpRxxU
s
)( max0
Source s:
s
lslslp
cxRpl
max0
Link l:
sllsss tpRUtx )()1( 1'
slslll ctxtptp )()()1(
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Synchronous convergence
Theorem (L & Lapsley 99)
Provided R has full row rank & Us strictly concave:
Gradient projection algorithm of dual problem
Converges to optimal primal-dual solutions if
Limit point: unique Pareto optimal Nash equilibrium
LSl 2
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Asynchronous convergence
Sources and links update & compute at different times with different frequencies using delayed info
Theorem (L & Lapsley 99)
Converges in asynchronous environment with smaller
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Equilibrium of VegasNetwork
Link queueing delays: pl
Queue length: clpl
Sources
Throughput: xi
E2E queueing delay : qi
Packets buffered:
Utility funtion: Ui(x) = i di log x Proportional fairness
iiii dqx
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Validation (L. Wang, Princeton)
Source rates (pkts/ms)# src1 src2 src3 src4 src51 5.98 (6) 2 2.05 (2) 3.92 (4)3 0.96 (0.94) 1.46 (1.49) 3.54 (3.57)4 0.51 (0.50) 0.72 (0.73) 1.34 (1.35) 3.38 (3.39)5 0.29 (0.29) 0.40 (0.40) 0.68 (0.67) 1.30 (1.30) 3.28
(3.34)
# queue (pkts) baseRTT (ms)1 19.8 (20) 10.18 (10.18)2 59.0 (60) 13.36 (13.51)3 127.3 (127) 20.17 (20.28)4 237.5 (238) 31.50 (31.50)5 416.3 (416) 49.86 (49.80)
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Methodology
Protocol (Reno, Vegas, RED, REM/PI…)
Equilibrium Performance
Throughput, loss, delay
Fairness Utility
Dynamics Local stability Cost of stabilization
))( ),(( )1(
))( ),(( )1(
txtpGtp
txtpFtx
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222
2
3
33
)1(4
)1 )(
2
-(Nc
N
c
Theorem (Low et al, Infocom’02) Reno/RED is locally stable if
Stability: Reno/RED
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
TCP: Small Small c Large N
RED: Small Large delay
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Stability: scalable control
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
lll
l ctyc
tp )(1
)()(
)(tq
mii
iii
i
extx
Theorem (Paganini, Doyle, L, CDC’01) Provided R is full rank, feedback loop is locally stable for arbitrary delay, capacity, load and topology
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Stability: Stabilized Vegas
)()(1)( tan)(
1 )()(1-
2tqtt
tTx iid
tqtxi ii
ii
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
lll
l ctyc
tp )(1
)(
Theorem (Choe & L, Infocom’03) Provided R is full rank, feedback loop is locally stable if
),( max aTx ii
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Stability: Stabilized Vegas
ii
ii
dtqtx
i tTx
)()(
21sgn
)(
1
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
lll
l ctyc
tp )(1
)(
Theorem (Choe & L, Infocom’03) Provided R is full rank, feedback loop is locally stable if
),( max aTx ii
-1
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Stability: FAST
)()(1)( tan)(
1 )()(1-
2tqtt
tTx iid
tqtxi ii
ii
F1
FN
G1
GL
Rf(s)
Rb’(s)
TCP Network AQM
x y
q p
lll
l ctyc
tp )(1
)(
Application Stabilized TCP with current routers Queueing delay as congestion measure has right scaling Incremental deployment with ECN
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Outline
Motivation Network model FAST TCP
Equilibrium Stability Experiments
TCP/IP
Applications
TCP/AQM
IP
Transmission
WWW, Email, Napster, FTP, …
Ethernet, ATM, POS, WDM, …
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Window control algorithm
Theorem (Jin, Wei, L ‘03) In absence of delay Mapping from w(t) to w(t+1) is contraction Global exponential convergence Full utilization after finite time Utility function: i log xi (proportional fairness)
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Network
(Sylvain Ravot, caltech/CERN)
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FAST BMPS
Internet2Land Speed
Record
FAST
1 2
1
2
7
9
10
Gen
eva-
Sunn
yval
e
Baltim
ore-S
unnyvale
#flows
FAST Standard MTU Throughput averaged over > 1hr
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Aggregate throughput
1 flow 2 flows 7 flows 9 flows 10 flows
Average utilization
95%
92%
90%
90%
88%FAST Standard MTU Utilization averaged over > 1hr
1hr 1hr 6hr 1.1hr 6hr
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Aggregate throughput
Linux TCP Linux TCP FAST
Average utilization
19%
27%
92%FAST Standard MTU Utilization averaged over 1hr
txq=100 txq=10000
95%
16%
48%
Linux TCP Linux TCP FAST
2G
1G
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SCinet Caltech-SLAC experiments
netlab.caltech.edu/FAST
SC2002 Baltimore, Nov 2002
Acknowledgments
PrototypeC. Jin, D. Wei
TheoryD. Choe (Postech/Caltech), J. Doyle, S. Low, F. Paganini (UCLA), J. Wang, Z. Wang (UCLA)
Experiment/facilities Caltech: J. Bunn, C. Chapman, C. Hu (Williams/Caltech), H. Newman, J. Pool, S.
Ravot (Caltech/CERN), S. Singh CERN: O. Martin, P. Moroni Cisco: B. Aiken, V. Doraiswami, R. Sepulveda, M. Turzanski, D. Walsten, S. Yip DataTAG: E. Martelli, J. P. Martin-Flatin Internet2: G. Almes, S. Corbato Level(3): P. Fernes, R. Struble SCinet: G. Goddard, J. Patton SLAC: G. Buhrmaster, R. Les Cottrell, C. Logg, I. Mei, W. Matthews, R. Mount, J.
Navratil, J. Williams StarLight: T. deFanti, L. Winkler
Major sponsorsARO, CACR, Cisco, DataTAG, DoE, Lee Center, NSF
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Dynamic sharing: 3 flowsFAST Linux
Dynamic sharing on Dummynet capacity = 800Mbps delay=120ms 3 flows iperf throughput Linux 2.4.x (HSTCP: UCL)
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Dynamic sharing: 3 flowsFAST Linux
HSTCP STCP
Steady throughput
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FAST Linux
throughput
loss
queue
STCPHSTCP
Dynamic sharing on Dummynet capacity = 800Mbps delay=120ms 14 flows iperf throughput Linux 2.4.x (HSTCP: UCL)
30min
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FAST Linux
throughput
loss
queue
STCPHSTCP
30min
Room for mice !
HSTCP
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Outline
Motivation Network model FAST TCP
Equilibrium Stability Experiments
TCP/IP
Applications
TCP/AQM
IP
Transmission
WWW, Email, Napster, FTP, …
Ethernet, ATM, POS, WDM, …
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Network model
F1
FN
G1
GL
R
RT
TCP Network AQM
x y
q p
))( ),(( )1(
))( ),(( )1(
tRxtpGtp
txtpRFtx T
Reno, Vegas
DT, RED, …
liRli link uses source if 1 IP routing
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Motivation
ll
li l
lliR
iiixp
iii
xR
cppRxxU
cRxxU
ii
max)( max min
subject to )( maxmax
00
0
:Dual
:Primal
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Motivation
Can TCP/IP maximize utility?
ll
li l
lliR
iiixp
iii
xR
cppRxxU
cRxxU
ii
max)( max min
subject to )( maxmax
00
0
:Dual
:Primal
Shortest path routing!
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TCP-AQM/IP
Theorem (Wang, et al 03)
Primal problem is NP-hard
Ai
iAi
i cc
Proof Reduce integer partition to primal problem
Given: integers {c1, …, cn}Find: set A s.t.
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TCP-AQM/IP
Theorem (Wang, et al 03)
Primal problem is NP-hard
Achievable utility of TCP/IP?
Stability? Duality gap?
Conclusion: Inevitable tradeoff between
achievable utility routing stability
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Ring networkdestination
r
Single destination Instant convergence of
TCP/IP Shortest path routing
Link cost = pl(t) + dl
price static
TCP/AQM
IPr(0)
pl(0)
r(1)
pl(1)
… r(t), r(t+1) , …
routing
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Ring networkdestination
r
TCP/AQM
IPr(0)
pl(0)
r(1)
pl(1)
… r(t), r(t+1) , …
Stability: r ?
Utility: V ?r* : optimal routing
V* : max utility
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Ring networkdestination
rTheorem (Infocom 2003)
“No” duality gap Unstable if = 0
starting from any r(0), subsequent r(t) oscillates between 0 and 1
link cost = pl(t) + dl
Stability: r ?
Utility: V ?
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Ring networkdestination
r
link cost = pl(t) + dl
0
0||*
*
VV
rr
Theorem (Infocom 2003)
Solve primal problem asymptoticallyas
Stability: r ?
Utility: V ?
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Ring networkdestination
r
link cost = pl(t) + dl
Theorem (Infocom 2003)
large: globally unstable small: globally stable medium: depends on r(0)
Stability: r ?
Utility: V ?
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General network
Conclusion: Inevitable tradeoff between
achievable utility routing stability
random graph20 nodes, 200 links Achievable
utility
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FAST TCP: motivation, architecture, algorithms, performance. submitted for publication, July 1, 2003
-release: August 2003Inquiry: [email protected]
FAST Project Review Caltech, Oct 27-28, 2003
netlab.caltech.edu/FAST