1. Networks Lab, Rensselaer Polytechnic Institute 1 LT-TCP: End-to-End Framework to Improve TCP Performance over Networks with Lossy Channels Omesh Tickoo, Vijay Subramanian,Shiv Kalyanaraman (Rensselaer Polytechnic Institute) K.K. Ramakrishnan (AT&T) Status Reports Packets, FEC Repairs Timeout

2. Networks Lab, Rensselaer Polytechnic Institute 2 Overview q TCP performance over wireless: q loss vs. congestion, heavy erasures q Building Blocks: q ECN congestion response q Adaptive maximum segment size (MSS) q Proactive and Reactive FEC q Performance Results: q Contribution of each building block q Comparisons to link-level support q Ongoing work

3. Networks Lab, Rensselaer Polytechnic Institute 3 TCP over wireless channels q TCP doesn’t distinguish between erasure and congestion loss q Bigger problem: TCP suffers significant timeout penalties with erasure rates > 5% q Qn: Can we “robustify” TCP to handle larger packet erasure rates: 30-50% ? q Wireless channels becoming more pervasive q With mesh networks (infrastructure or community) it is likely that more than the last hop will be wireless q Cannot just use the cross-layer techniques like TCP performance enhancing proxies (PEPs) to “fix” TCP’s performance

4. Networks Lab, Rensselaer Polytechnic Institute 4 SENDERSENDER RECEIVERRECEIVER Available Capacity Loss Feedback Through Acknowledgements Capacity Used TCP uses Loss Feedback to Estimate Available Capacity Capacity Used Interpreting Transmission Losses as Congestion Leads to Capacity Under-Estimation Capacity Used Erasure Recovery/ Loss Estimation Adaptive MSS/ Proactive and Reactive FEC LT-TCP: Adaptive Mechanisms to Reinstate Performance XX X – Packet Erasure

5. Networks Lab, Rensselaer Polytechnic Institute 5 Transport/Link Layer: Standard Reliability Model Packets Sequence Numbers CRC or Checksum Proactive FEC Status Reports ACKs NAKs, dupacks SACKs Bitmaps Rexmitted Packets Reactive FEC Repair pkts Timeout

6. Networks Lab, Rensselaer Polytechnic Institute 6 Reed-Solomon FEC: RS(N,K) Data = K FEC (N-K) Block Size (N) RS(N,K) >= K of N received Lossy Network Recover K data packets!

7. Networks Lab, Rensselaer Polytechnic Institute 7 Building Blocks: Goals q Congestion Response: q How should TCP respond to congestion notifications, q … but not respond to packet erasures that do not signal congestion? q Mix of Reliability Mechanisms: q What mix of TCP repair mechanisms should be used to achieve the TCP reliability objectives ? q What is the role of error correction (FEC) ? q How should be split between proactive and reactive repair? q Timeouts: q Timeouts: final fallback mechanism, but wasteful otherwise. q How to structure the mix to reduce timeouts?

8. Networks Lab, Rensselaer Polytechnic Institute 8 Building Blocks: Design q Congestion: respond only to ECN q Assumes ECN-enabled networks q Window granulation: at least G q Smaller PER for a given BER q More dupacks per burst loss event (SACK requires at least 3 dupacks) q MSS is adaptive. q FEC per-window: q Shortened RS-codes (see next slide) q Proactive FEC based upon estimate of per-window loss rate (Adaptive) q Reactive FEC to protect retransmissions q FEC packets can correct any data packets: totally K out of N needs to reach receiver q Timeout avoidance turns out to be harder than distinguishing erasure from congestion

9. Networks Lab, Rensselaer Polytechnic Institute 9 Shortened Reed Solomon FEC (per-Window) Proactive FEC (F) Data = d Window (W) Reactive FEC (R) 0 0 0 0 0 0 Zeros (z) Block Size (N) K = d + z d z RS(N,K)

10. Networks Lab, Rensselaer Polytechnic Institute 10 5 4 3 2 1 4321 Complete Window Lost! Window XXXX Transmission Loss Timout Cause #1: Burst Errors + Large MSS

11. Networks Lab, Rensselaer Polytechnic Institute 11 1 Window XXXX Transmission Loss 2 3 4 5 6 7 7654321 127 ACK Stream (assuming selective ACK) 654 Rexmins 3 Window Granulation Reduces the Risk of Losing the Complete Window

12. Networks Lab, Rensselaer Polytechnic Institute 12 1 XX Transmission Loss 654321 Window 2 3 4 5 6 1 ACK Stream 2 DUPACK-1 Timeout because of insufficient dupacks 2 Timout Cause #2: Insufficient Dupacks => SACK not triggered X

13. Networks Lab, Rensselaer Polytechnic Institute 13 1 XX Transmission Loss P-FEC 4321 Window 2 3 4 P-FEC Receiver FEC Decoder P-FEC 21 +++ 4321 Proactive FEC Reduces the Need for Dupacks Recover data packets…

14. Networks Lab, Rensselaer Polytechnic Institute 14 3 Window Transmission Loss XX 65421 2 1 3 4 5 6 1 ACK Stream 1 DUPACK-3 11 DUPACK-1DUPACK-2 2 Retransmission X Transmission Loss ReXMITS ESPECIALLY vulnerable! Timeout Cause #3: Loss of Retransmissions

15. Networks Lab, Rensselaer Polytechnic Institute 15 1 XX Transmissio n Loss 654321 Window 2 3 4 5 6 1 ACK Stream 6 DUPACK-3 54 DUPACK-1DUPACK-2 R-FEC Receiver FEC Decoder R-FEC 41 +++ 4321 Reactive FEC: Protects Rexmits

16. Networks Lab, Rensselaer Polytechnic Institute 16 Loss Estimate FEC Computation (n,k) Parameter Estimation MSS Adaptation Granulated Window Size Window Size Application Data P-FEC Data Window Putting it Together….

17. Networks Lab, Rensselaer Polytechnic Institute 17 Building Block Behavior: Adaptive MSS (Window Granulation)  Congestion window (in segments) kept above G = 10  MSS increases when CWND grows,  MSS shrinks when CWND shrinks to maintain G

18. Networks Lab, Rensselaer Polytechnic Institute 18 Packet Erasure Rate EWMA Estimator: E =  *E latest + (1-  )*E Estimate is fairly accurate within small erasure rate variations Overestimate after spikes :  = E latest / (E latest + E) Trade off :Over- estimation leads to overhead. Overestimate Inefficiency Period BBlock Behavior: Per-Window Loss Estimator for P-FEC

19. Networks Lab, Rensselaer Polytechnic Institute 19 Simulation Configuration Lumped model: view multiple bottlenecks as 1 aggregate bottleneck

20. Networks Lab, Rensselaer Polytechnic Institute 20 Performance Results SACK LT-TCP:

21. Networks Lab, Rensselaer Polytechnic Institute 21 Performance Results (Contd)

22. Networks Lab, Rensselaer Polytechnic Institute 22 Contribution of Components (10% PER case) Source of gains: #1: Timeout reduction #2: Distinguishing erasures from congestion (w/ ECN)

23. Networks Lab, Rensselaer Polytechnic Institute 23 Comparison w/ Link Layer FEC, HARQ LL FEC: adaptive FEC based upon average PER HARQ: 10% FEC; ARQ persistence = 3 LT-TCP: end-to-end

24. Networks Lab, Rensselaer Polytechnic Institute 24 Summary TCP performance over wireless: residual erasure rates > 5% (short- or long-term) q E2E H-ARQ: q Granulation ensures better flow of ACKs especially in small window regime. q Adaptive FEC (proactive and reactive) can protect critical packets appropriately q Adaptive => No overhead when there is no loss q ECN to distinguish congestion from loss q Future Work: q Handle higher erasure rates (30%+) better q Optimal division of reliability functions between PHY,MAC, E2E

25. Networks Lab, Rensselaer Polytechnic Institute 25 Thanks! Researchers: Omesh Tickoo: tickoo@rpi.edutickoo@rpi.edu Vijay Subramanian: subrav@rpi.edusubrav@rpi.edu Shiv Kalyanaraman: shivkuma@rpi.edushivkuma@rpi.edu K.K. Ramakrishnan, kkrama@research.att.com kkrama@research.att.com