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FAST TCP Cheng Jin David Wei Steven Low netlab.CALTECH.edu GNEW, CERN, March 2004.

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Presentation on theme: "FAST TCP Cheng Jin David Wei Steven Low netlab.CALTECH.edu GNEW, CERN, March 2004."— Presentation transcript:

1 FAST TCP Cheng Jin David Wei Steven Low netlab.CALTECH.edu GNEW, CERN, March 2004

2 Acknowledgments  Caltech Bunn, Choe, Doyle, Jin, Newman, Ravot, Singh, J. Wang, Wei  UCLA Paganini, Z. Wang  CERN/DataTAG Martin, Martin-Flatin  Internet2 Almes, Shalunov  SLAC Cottrell, Mount  Cisco Aiken, Doraiswami, Yip  Level(3) Fernes  LANL Wu

3 FAST project Performance StabilityFairnessTCP/IPNoise Random -ness Theory Linux TCP kernel Other platforms Monitoring Debugging Implement Abilene PlanetL DummyNet HEP networks WAN in Lab UltraLight testbed Experiment TeraGridHEP networksAbilene IETF GGF Deployment NSF ITR (2001) NSF STI (2002) NSF RI (2003)

4 Outline  Experiments Results Future plan  Status Open issues Code release mid 04  Unified framework Reno, FAST, HSTCP, STCP, XCP, … Implementation issues

5 FAST TCP util: 95% Linux TCP (no tuning) util: 19% 1Gbps path; 180 ms RTT; 1 flow Jin, Wei, Ravot, etc (Caltech, Nov 02) DataTAG: CERN – StarLight – Level3/SLAC

6 Aggregate throughput 1 flow 2 flows 7 flows 9 flows 10 flows Average utilization 95% 92% 90% 88% FAST  Standard MTU  Utilization averaged over > 1hr 1hr 6hr 1.1hr6hr DataTAG: CERN – StarLight – Level3/SLAC (Jin, Wei, Ravot, etc SC2002)

7 Dynamic sharing: 3 flows FASTLinux Dynamic sharing on Dummynet  capacity = 800Mbps  delay=120ms  3 flows  iperf throughput  Linux 2.4.x (HSTCP: UCL)

8 Dynamic sharing: 3 flows FASTLinux HSTCPSTCP Steady throughput

9 FASTLinux throughput loss queue STCPHSTCP Dynamic sharing on Dummynet  capacity = 800Mbps  delay=120ms  14 flows  iperf throughput  Linux 2.4.x (HSTCP: UCL) 30min

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

11 Aggregate throughput ideal performance Dummynet: cap = 800Mbps; delay = 50-200ms; #flows = 1-14; 29 expts

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

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

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

15 Outline  Experiments Results Future plan  Status Open issues Code release  Unified framework Reno, FAST, HSTCP, STCP, XCP, … Implementation issues

16 Benchmarking TCP  Not just static throughput Dynamic sharing, what protocol does to network, …  Tests to zoom in on specific properties Throughput, delay, loss, fairness, stability, … Critical for basic design Test scenarios may not be realistic  Tests with realistic scenarios Same performance metrics Critical for refinement for deployment Just started  Input solicited What’s realistic for your applications?

17 Open issues: well understood  baseRTT 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 should react? rare for large transfer?

18 Status: code release  Source release mid 2004 For any non-profit purposes Re-implementation of FAST TCP completed Extensive testing to complete by April 04  Pre-release trials CFP for high-performance sites!  Incorporate into Web100 with Matt Mathis

19 Status: IPR Caltech will license royalty-free if FAST TCP becomes IETF standard IPR covers more broadly than TCP Leave all options open

20 Outline  Experiments Results Future plan  Status Open issues Code release mid 04  Unified framework Reno, FAST, HSTCP, STCP, XCP, … Implementation issues

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

22 Reno TCP  Packet level Designed and implemented first  Flow level Understood afterwards  Flow level dynamics determines Equilibrium: performance, fairness Stability  Design flow level equilibrium & stability  Implement flow level goals at packet level

23 Reno TCP  Packet level Designed and implemented first  Flow level Understood afterwards  Flow level dynamics determines Equilibrium: performance, fairness Stability Packet level design of FAST, HSTCP, STCP, H-TCP, … guided by flow level properties

24 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

25 Flow level: Reno, HSTCP, STCP, FAST  Similar flow level equilibrium  = 1.225 (Reno), 0.120 (HSTCP), 0.075 (STCP) MSS/sec

26 Flow level: Reno, HSTCP, STCP, FAST  Different gain  and utility U i They determine equilibrium and stability  Different congestion measure p i Loss probability (Reno, HSTCP, STCP) Queueing delay (Vegas, FAST)  Common flow level dynamics window adjustment control gain flow level goal =

27 FAST TCP  Reno, HSTCP, and FAST have common flow level dynamics window adjustment control gain flow level goal =  Equation-based Need to estimate “price” p i (t)  p i (t) = queueing delay Easier to estimate at large window   (t) and U’ i (t) explicitly designed for Performance Fairness Stability

28 Architecture Each component  designed independently  upgraded asynchronously

29 Architecture Each component  designed independently  upgraded asynchronously Window Control

30 Window control algorithm  Full utilization regardless of bandwidth-delay product  Globally stable exponential convergence  Intra-protocol fairness weighted proportional fairness parameter 

31 FAST tunes to knee TCP oscillation FAST stabilized Goal: Less delay Less jitter

32 Window adjustment FAST TCP

33  FAST TCP: motivation, architecture, algorithms, performance IEEE Infocom March 2004  FAST TCP: from theory to experiments Submitted for publication April 2003 netlab.caltech.edu/FAST

34 Panel 1: Lessons in Grid Networking

35 Metrics  Performance Throughput, loss, delay, jitter, stability, responsiveness  Availability, reliability  Simplicity Application Management  Evolvability, robustness

36 Constraints  Scientific community Small & fixed set of major sites Few & large transfers Relatively simple traffic characteristics and quality requirements  General public Large, dynamic sets of users Diverse set of traffic characteristics & quality requirements Evolving/unpredictable applications

37 Mechanisms  Fiber infrastructure  Lightpath configuration  Resource provisioning  Traffic engineering, adm control  Congestion/flow control Months - years Mintes - days Service: sec - hrs Flow: sec - mins RTT: ms - sec  Timescale: desired, instead of feasible  Balance: cost/benefit, simplicity, evolvability


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