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FAST TCP

FAST TCP. Design, architecture, algorithms Experimental evaluations. Lachlan Andrew (for Steven Low) netlab. CALTECH .edu. Acks & Collaborators. Internet2 Almes, Shalunov Abilene GigaPoP’s GATech, NCSU, PSC, Seattle, Washington Cisco Aiken, Doraiswami, McGugan, Smith, Yip Level(3)

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FAST TCP

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  1. FAST TCP Design, architecture, algorithms Experimental evaluations Lachlan Andrew(for Steven Low) netlab.CALTECH.edu

  2. Acks & Collaborators • Internet2 • Almes, Shalunov • Abilene GigaPoP’s • GATech, NCSU, PSC, Seattle, Washington • Cisco • Aiken, Doraiswami, McGugan, Smith, Yip • Level(3) • Fernes • LANL • Wu • Caltech • Andrew, Bunn, Choe, Doyle, Hegde, Jin, Li, Low, Newman, Papadoupoulous, Ravot, Singh, Tang, J. Wang, Wei, Wydrowski, Xia • UCLA • Paganini, Z. Wang • StarLight • deFanti, Winkler • CERN • Martin • SLAC • Cottrell • PSC • Mathis

  3. pl(t) • AQM: • DropTail • RED • REM/PI • AVQ xi(t) TCP: • Reno • Vegas 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

  4. Packet & flow level Reno TCP FAST, BIC, H-TCP • Packet level - first • Packet level Implement flow behavior ACK: W  W + 1/W Loss: W  W – 0.5W • Flow level • Equilibrium • Fairness, performance • Dynamics • Stability Understood later • Flow level • Equilibrium • Dynamics Design for equilibrium and stability

  5. Flow level: Reno, HSTCP, STCP, FAST • Similarflow level equilibrium • , b, c determine equilibrium • Commonflow level dynamics! window adjustment control gain flow level goal = • Different gain k and utility Ui • Determine equilibrium and stability • Different congestion measure pi • Loss probability (Reno, HSTCP, STCP) • Queueing delay (Vegas, FAST) • Loss pattern in BIC, HTPC,… Combination in CTCP

  6. <RTT timescale RTT timescale Loss recovery FAST Architecture Loss Control

  7. Window control algorithm • Feedback is Queueing Delay, not Loss Theorem(Infocom04, CDC04, Infocom05, Infocom07) • Full utilization • regardless of bandwidth-delay product • Globally stable • exponential convergence • Fairness • weighted proportional fairness, parameter a • Utility function ai log (wi/RTTi)

  8. Isn’t FAST just like Vegas? • Similarities • Feedback is Queueing Delay, not Loss • Same equilibrium • Differences • New dynamics • Change proportional to error • Responds much faster when flows come/go • Implementation details: Burstiness control rate time

  9. RTT RTT = 400ms double baseRTT FAST Throughput Yusung Kim, KAIST, Korea 10/2004 • All can achieve high throughput except Reno • FAST adds negligible queueing delay • Loss-based control (almost) fills buffer … • adding delay and reducing ability to absorb bursts HSTCP BIC

  10. Wireless Networking max FAST B. Wydrowski S. Hegde Caltech, April 2005 (%)

  11. Delay based control • Need not fill buffers • Less delay, can absorb bursts • Control rates but can ignore loss • Less need to over-engineer links • Continuous feedback • no window-halving • Neither more nor less conservative • “Network equilibrium of heterogeneous congestion control protocols”Tang et al., INFOCOM, 2005 • Depends on buffer sizes vs link speeds • Can have multiple equilibria

  12. Conclusion • Mathematically, FAST fits into the standard TCP/AQM framework • AQM signal is delay • High utilisation with small queues • Insensitive to loss • Stable • No window halving • Control-theoretically stable

  13. Dynamic sharing: 3 flows FAST Linux Reno Steady throughput HSTCP BIC

  14. 30min queue Room for mice ! FAST Linux loss throughput HSTCP HSTCP BIC

  15. Is large queue necessary for high throughput?

  16. DSL upload, 4/28/2005 11:15-11:38am • Min RTT: 18ms (File size: 16.6MB) • DSL upload (6Mbps/512kbps), 5/2005 • Min RTT: 10ms

  17. “Ultrascale” protocol development: FASTTCP FAST TCP • Based on TCP Vegas • Uses end-to-end delay and loss to dynamically adjust the congestion window • Defines an explicit equilibrium Capacity = OC-192 9.5Gbps; 264 ms round trip latency; 1 flow BW use 50% BW use 79% BW use 30% BW use 40% Linux TCP Westwood+BIC TCP FAST (Yang Xia, Caltech)

  18. FAST backs off to make room for Reno Periodic losses every 10mins (Yang Xia, Harvey Newman, Caltech)

  19. I2LSR, SC2004 Bandwidth Challenge Harvey Newman’s group, Caltech http://dnae.home.cern.ch/dnae/lsr4-nov04 OC48 OC192 November 8, 2004 Caltech and CERN transferred • 2,881 GBytes in one hour (6.86Gbps) • between Geneva - US - Geneva (25,280 km) • through LHCnet/DataTag, Abilene and CENIC backbones • using 18 FAST TCP streams • on Linux 2.6.9 kernel with 9000KB MTU • at 174 Pbm/s

  20. Algorithm, prototype • window control • loss control • burstiness control • Experiment • HEP • networking • WAN in Lab algorithm prototype application experiment • Theory • general large scale network • performance, fairness, dynamics theory • Theory • heterogeneous protocols • TCP/IP interactions • Alg, prototype • a –tuning • loadable kernel module • Application • make robust • support deployment

  21. FAST Architecture Each component • designed independently • upgraded asynchronously Loss Control

  22. Window control algorithm Theorem(Infocom04, CDC04, Infocom05) • Mapping from w(t) to w(t+1) is contraction • Global exponential convergence • Full utilization after finite time • Utility function: ai log xi (proportional fairness)

  23. Wireless Networking FAST B. Wydrowski S. Hegde Caltech, April 2005 (%)

  24. Internet2 Abilene Weather Map OC48 OC192 7.1G: GENV-PITS-LOSA-SNVA-STTL-DNVR-KSCY-HSTON-ATLA-WASH-NYCM-CHIN-GENV Newman’s group, Caltech

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