1. Cheng Jin David Wei Steven Low http://netlab.caltech.edu FAST TCP: design and experiments

2. Performance at large windows capacity = 155Mbps, 622Mbps, 2.5Gbps, 5Gbps, 10Gbps; 100 ms round trip latency; 100 flows J. Wang (Caltech, June 02) ns-2 simulation 10Gbps 27% txq=100txq=10000 95% 1G Linux TCP Linux TCP FAST 19% average utilization capacity = 1Gbps; 180 ms round trip latency; 1 flow C. Jin, D. Wei, S. Ravot, etc (Caltech, Nov 02) DataTAG Network: CERN (Geneva) – StarLight (Chicago) – SLAC/Level3 (Sunnyvale) txq=100

3. Packet & flow level ACK: W  W + 1/W Loss: W  W – 0.5W  Packet level Reno TCP  Flow level Equilibrium Dynamics packets (Mathis formula)

4. Difficulties at large window  Equilibrium problem Packet level: AI too slow, MI too drastic. Flow level: requires very small loss probability.  Dynamic problem Packet level: must oscillate on a binary signal. Flow level: unstable at large window.

5. Problem: binary signal TCP oscillation

6. Solution: multibit signal FAST stabilized

7. Problem: no target ACK: W  W + 1/W Loss: W  W – 0.5W  Reno: AIMD (1, 0.5) ACK: W  W + a(w)/W Loss: W  W – b(w)W ACK: W  W + 0.01 Loss: W  W – 0.125W  HSTCP: AIMD (a(w), b(w))  STCP : MIMD (1/100, 1/8)

8. Solution: estimate target  FAST Slow Start FAST Conv Equil Loss Rec Scalable to any w*

9. Packet level ACK: W  W + 1/W Loss: W  W – 0.5W  Reno AIMD(1, 0.5) ACK: W  W + a(w)/W Loss: W  W – b(w)W  HSTCP AIMD(a(w), b(w)) ACK: W  W + 0.01 Loss: W  W – 0.125W  STCP MIMD(a, b)  FAST

10. FAST TCP  Flow level Understood and Synthesized first.  Packet level Designed and implemented later.  Design flow level equilibrium & stability  Implement flow level goals at packet level

11. Architecture ~ RTT timescale Ack timescale ~ Ack timescale Data Control Window Control Burstiness Control Estimation TCP Protocol Processing

12. Architecture Each component  designed independently  upgraded asynchronously Data Control Window Control Burstiness Control Estimation TCP Protocol Processing

13. Dynamic sharing: 3 flows FASTLinux HSTCPSTCP Steady throughput

14. FASTLinux throughput loss queue STCPHSTCP 30min Room for mice ! HSTCP

15. Aggregate throughput small window 800pkts large window 8000 Dummynet: cap = 800Mbps; delay = 50-200ms; #flows = 1-14; 29 expts

16. Fairness Jain’s index HSTCP ~ Reno Dummynet: cap = 800Mbps; delay = 50-200ms; #flows = 1-14; 29 expts

17. Stability Dummynet: cap = 800Mbps; delay = 50-200ms; #flows = 1-14; 29 expts stable in diverse scenarios

18. Open issues  network latency estimation route changes, dynamic sharing does not upset stability  small network buffer at least like TCP adapt on slow timescale, but how?  TCP-friendliness friendly at least at small window tunable, but how to tune?  reverse path congestion

19. What can FAST do?  Networks that support large windows Long latency High bandwidth  Networks experience moderate packet losses  HTTP traffic  Low-bandwidth networks and LANs

20. Acknowledgments  Caltech Bunn, Choe, Doyle, Newman, Ravot, Singh, J. Wang  UCLA Paganini, Z. Wang  CERN Martin  SLAC Cottrell  Internet2 Almes, Shalunov  Cisco Aiken, Doraiswami, Yip  Level(3) Fernes  LANL Wu