1 / 25

LT-TCP: End-to-End Framework to Improve TCP Performance over Networks with Lossy Channels

Packets, FEC. Timeout. Status Reports. Repairs. 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). Overview.

zenia
Download Presentation

LT-TCP: End-to-End Framework to Improve TCP Performance over Networks with Lossy Channels

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Packets, FEC Timeout Status Reports Repairs 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)

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

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

  4. TCP uses Loss Feedback to Estimate Available Capacity Interpreting Transmission Losses as Congestion Leads to Capacity Under-Estimation LT-TCP: Adaptive Mechanisms to Reinstate Performance Adaptive MSS/ Proactive and Reactive FEC Erasure Recovery/ Loss Estimation Capacity Used Capacity Used Capacity Used Available Capacity RECEIVER SENDER X X Loss Feedback Through Acknowledgements X – Packet Erasure

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

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

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

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

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

  10. Timout Cause #1: Burst Errors + Large MSS 5 4 Window 3 4 3 2 1 2 Transmission Loss 1 X X X X Complete Window Lost!

  11. Window Granulation Reduces the Risk of Losing the Complete Window 7 6 5 Window 7 6 5 4 3 2 1 4 3 2 Transmission Loss X X X X 1 1 2 7 ACK Stream (assuming selective ACK) 6 5 4 3 Rexmins

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

  13. 4 3 2 1 Proactive FEC Reduces the Need for Dupacks P-FEC P-FEC 4 Window P-FEC P-FEC 4 3 2 1 3 2 Transmission Loss X X 1 Receiver FEC Decoder + + + P-FEC P-FEC 2 1 Recover data packets…

  14. 5 6 5 4 2 1 4 3 X X 2 1 Transmission Loss Timeout Cause #3: Loss of Retransmissions 6 Window 3 1 1 1 1 ACK Stream DUPACK-1 DUPACK-2 DUPACK-3 Retransmission 2 Transmission Loss X ReXMITS ESPECIALLY vulnerable!

  15. Reactive FEC: Protects Rexmits 6 5 Window 4 6 5 4 3 2 1 3 2 Transmission Loss X X 1 1 4 5 6 ACK Stream DUPACK-1 DUPACK-2 DUPACK-3 R-FEC R-FEC Receiver FEC Decoder + + + R-FEC R-FEC 4 1 4 3 2 1

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

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

  19. Simulation Configuration Lumped model: view multiple bottlenecks as 1 aggregate bottleneck

  20. SACK LT-TCP: Performance Results

  21. Performance Results (Contd)

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

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

  25. Thanks! Researchers: Omesh Tickoo: tickoo@rpi.edu Vijay Subramanian: subrav@rpi.edu Shiv Kalyanaraman: shivkuma@rpi.edu K.K. Ramakrishnan, kkrama@research.att.com

More Related