The Role of PCE in the Evolution of Transport Protocols

1. The Role of PCE in the Evolution of Transport Protocols Pfldnet 2005, Lyon, France M. Y. “Medy” Sanadidi http://www.cs.ucla.edu/~medy http://www.cs.ucla.edu/NRL/hpi/tcpw/ Proprietary Content

2. Recent Issues in Transport Protocols • Large Pipes Utilization • Steady state • Start-up • Impact of Wireless Links: • Last-hop wireless • Multihop contention networks • Fairness for asymmetric flows • Protocols Co-Existence • New Paradigms: • Voice/Video • Store-and-forward at Transport layer (e.g. PEPs, P2P/Overlays) Proprietary Content

3. Example: Satellite/802.11 Networks Proprietary Content

4. Outline • Path Characteristics Estimation (PCE) • Prospects for Higher Efficiency • Future of Friendly Co-Existence • Addressing the New Paradigms • Summary Proprietary Content

5. Path Characteristics Estimation (PCE) • Characteristics of Interest: • Links capacity • Path ‘dynamic range’, i.e. buffering capacity • Cross traffic level, path-persistence, responsiveness • Random loss • Multihop wireless connectivity, contention, route diversity • Participating Nodes: • Sources only • Sources and Destinations • Forwarding nodes (routers, base stations, multihop wireless nodes) Proprietary Content

6. Sharing a Link interface queue Buffer space backlog bottleneck residual bandwidth Flow2 bandwidth 2 flows, red one is non-responsive Flow1 fair share ? Propagation Time Proprietary Content

7. A Hierarchy of Characteristics • Achieved rate • Delay/Dynamic Range • Packet loss Flow Behavior • Intensity • Path persistence • Elasticity Cross Traffic Load + • Links capacities • Propagation times • Buffer space • Errors Architecture Proprietary Content

8. Path Capacity Estimation • Path Capacity: capacity of narrow link • Pathrate: rely on packet pair dispersion measurements followed by statistical processing of results • CapProbe: use dispersion measurements; perform on line filtering of results based on end-to-end delay • TcpProbe: an adaptation of CapProbe into TCP with minimal sender side only changes Proprietary Content

9. CapProbe: DelAck TCP Probe: CapProbe and TcpProbe Proprietary Content

10. Prospects for Higher Efficiency • Steady State: • Congestion avoidance (FAST): stable at high throughput, co-existence ??, and random loss impact ?? • Scaling up congestion recovery (HSTCP, STCP): higher throughput, but fairness and stability ?? • Scaling up congestion recovery (BIC): improves on the above in fairness • Forwarder Based (XCP): superb, when we are done with implementation issues • PCE reliance (TCP Westwood, TCP Peach): Peach requires forwarder priority support, TCPW requires good estimation at high speeds Proprietary Content

11. Using PCE • Tahoe/Reno/NewReno estimate: • Packet loss via Dup Acks • RTT average and variance • Maintain a pipe size (or bandwidth-delay product) estimate: ssthresh • Vegas/FAST: • Achieved Rate and its relation to the Expected Rate, or equivalently RTT and RTTmin, or Queuing delay • HSTCP/STCP/BIC: • Use current window size (Expected Rate) in addition to all items above in Reno Proprietary Content

12. Using PCE (2) • TCPW estimates • Packet loss and type of loss • Narrow link capacity, or Path capacity • Achieved Rate • “Dynamic Range” resulting from buffering space: (RTTmax-RTTmin) • XCP measures at forwarders the actual: • Links capacities • Load intensity • RTT (obtained from sources) Proprietary Content

13. Large Pipes Measurements Results Proprietary Content

14. Acceptable Long Term Efficiency Proprietary Content

15. Some Difference in Completion Times Proprietary Content

16. Co-Existence at Gbps Speed Proprietary Content

17. Random Loss Impact Proprietary Content

18. Effect of Random Loss Proprietary Content

19. TCPW: Mining ACK Streams for PCE • Rely on PCE ( e.g. capacity, achieved rate, dynamic range) to determine an Eligible Rate Estimate (ERE) • ERE is used to size the congestion window after a packet loss Bottleneck packets Receiver Sender ACKs Internet measure Proprietary Content

20. Tk TCPW BE (2001) BE Sampling: • With Saverio Mascolo (P. Bari) and Claudio Casetti (P. Torino) • ~ Packet pair • a noisy estimate of achieved rate/capacity • Provides throughput boost under random loss, overestimates under congestion • Efficient but not friendly Proprietary Content

21. Tk TCPW RE (2002) • RE Sampling: • ~ Packet train • Fair estimate under congestion, underestimates under random loss • Used in TCPW RE and inTCP Westwood+ (S. Mascolo) • Friendly Proprietary Content

22. Adaptive Estimation in TCPW TCPW CRB: ERE  BE if random loss, else ERE RE TCPW ABSE: ERE  RE<X <BE by continuously adapting the bandwidth sample width to congestion level TCPW Astart: use ERE to help short lived flows TCPW BBE: ERE  u * C + (1-u) * RE, where uis a congestion measure taking into account path dynamic range Proprietary Content

23. Binary adaptation TCPW CRB (2002) • Combined “Rate” and “Bandwidth” • Binary adaptive • Congestion measure: Expected Rate/Achieved Rate • Clarified Efficiency/Friendliness tradeoff over a threshold  ssthresh, cwnd = BE x RTTmin Packet Loss Detected Congestionmeasure Ssthresh, cwnd = RE x RTTmin under a threshold  Proprietary Content

24. Tk Tk TCPW ABSE (2002) Under No Congestion Under Congestion • Adaptive Bandwidth Share Estimation • Adapt the sample intervalTk according to congestion level • Congestion measure, similar to Vegas • Tk ranges from one ‘interACK’ interval to current RTT • Better Efficiency/Friendliness profile than CRB Proprietary Content

25. Helping Short Lived Connections • Approaches: • Cached ssthresh • Larger initial window • PCE based: Hoe’s; TCPW Astart • Negotiation: Quick-Start • No problems here for XCP! Proprietary Content

26. 510 cwnd 500 Linear increase phases 490 480 470 cwnd in packets 460 450 440 Exponential increase phases 430 420 1.6 1.7 1.8 1.9 2 2.1 2.2 Time (sec) TCPW Astart (2003) • Take advantage of ERE : Adaptively and repeatedly reset ssthresh ERE until sender window reaches estimated pipe size, or encounters packet loss • Includes multiple mini ‘exponential increase’, and mini ‘linear increase’ phases • cwnd grows slower as it approaches BDP • Connection converges faster to its pipe size with less buffer overflow, since it adapts to pipe size and transient loading Proprietary Content

27. Astart: First 20 Seconds Throughput • Good scaling with capacity and propagation time • Robust to buffer size variation RTT =100ms, Buffer =BDP Bottleneck capacity = 40 Mbps, Buffer =BDP RTT =100ms, Bottleneck =40 Mbps Proprietary Content

28. TCPW BBE (Work in Progress) • With H. Shimonishi (NEC, Tokyo) • “Buffer” and “Bandwidth” Estimation • Estimates Capacity using TcpProbe (much more accurate than BE!!) • Higher efficiency at higher random loss rates (e.g. 5-10%) • Estimates Dynamic Range (related to buffer size) • Improves TCPW control as a function of congestion • The result is higher efficiency and robust friendliness even at small buffers! Proprietary Content

29. Relative Frequency RTTcong_loss RTTmin Congestion loss Random loss RTT beforepacket loss TCPW BBE Algorithms (ICC 2005) Dynamic Range estimate Dmax = RTTcong loss - RTTmin Current Delay Distance D = RTT– RTTmin Eligible Rate estimate ERE = u * C + (1-u) * RE Note: u=0 if D and Dmax are small Proprietary Content

30. Opportunistic Friendliness of TCPW-BBE If Reno under-perform:use all the opportunity provided without hurting co-existing Reno flows TCP-Reno Sender Receiver RTT 40msec 0.001% loss 10M-1Gbps Receiver TCPW-BBE Sender If Reno performs:achieve similar to Reno Proprietary Content

31. The Future of Friendly Co-Existence • Defining Friendliness: • TCP Friendliness: • Achieve throughput equal to that of TCP Reno under some conditions (RTT, packet loss rate) • Problematic if Reno under-perform; e.g. under random losses • Opportunistic Friendliness: • If Reno performs, achieve similar to Reno • If Reno under-perform: use all the opportunity provided without hurting co-existing Reno flows Proprietary Content

32. Evaluating a New Proposed Protocol:The Efficiency/Friendliness Profile Each point in the graph is obtained as follows: • N legacy flows => • legacy throughput tR1 • total utilization U1 • N/2 legacy, N/2 proposed flows => • legacy throughput tR2 • Total utilization U2 • Efficiency Improvement E = U2 / U1 • Friendliness F = tR2 / tR1 Proprietary Content

33. E/F Profiles of TCPW BE, CRB and ABSE Proprietary Content

34. E/F Profile of Vegas 1.5 Vegas vs. NewReno (RED) 1.4 1.3 Utilization Ratio G (Efficiency) N=16 N=8 1.2 N=4 N=24 N=2 1.1 1 0.4 0.6 0.8 1 1.2 1.4 Throughput Ratio L (Friendliness) Vegas uses fixed targeted queue length => varying friendliness depending on number of connections! Proprietary Content

35. Addressing New Paradigms • Audio/Video Streaming: Increasing portion of the total traffic with distinct requirements • Multihop Wireless: Difficult fundamental issues • Store-and-forward at the Transport Layer: Revisit early problems and new opportunities Proprietary Content

36. Continuous Media Transport • Requirements: • Minimum bandwidth • Upper bound on delay • Lower reliability requirements than in FTP • Adaptive streaming objectives: • Delivered quality • Congestion control • Support for adaptive coding Proprietary Content

37. Addressing Continuous Media Issues • Issues with the standard protocols: • UDP: no congestion or error control • TCP: AIMD behavior undesirable due to fluctuation in rate, and consequently delay, and intolerance to random loss • DCCP provides an excellent framework, recommends TFRCas one possible protocol, but allows for alternatives • TFRC is equation based, rate-equivalent to Reno, with smoother delivery suitable for streaming • SCTPenables multiple streams with different congestion control mechanisms, among other features Proprietary Content

38. Streaming Over Wireless • Under random loss, Reno and its rate-equivalent TFRC, will both under-perform • Approaches, some with loss discrimination, have been proposed: • TFRC Wireless: Combination of loss discrimination schemes, • Multi-TFRC Multiple TFRC connections until link is congested • VTP Rate estimation and loss discrimination Proprietary Content

39. Performance Comparison Efficiency in presence of errors5% error rate, single connection Rate adaptation5% error rate, single connectionwith on/off CBR cross traffic Proprietary Content

40. TCP over Multihop Wireless • Packet losses due to: • Contention due to hidden terminals • Varying channel quality • Route collapse • Buffer overflow ?? • Solution approaches: • Neighborhood RED • Delayed ACK extension • Sizing the TCP window for contention reduction Proprietary Content

41. Store & Forward at the Transport Layer • Overlays/P2P tunneling through TCP connections • PEPs breaking ETE path into concatenated TCP connections, e.g. satellites • New(?) Requirements: • Buffer management and priority schemes for better ETE application protocol performance • TCP Receiver advertised window role • Related item: Prioritized TCP for QOS at the Transport layer (TCP-LP, TCPW-LP) Proprietary Content

42. Summary • Excellent progress by many approaches for scaling efficiency with pipe size • Focus on PCE techniques is promising, e.g. TCPW provides: • Scalable efficiency • Robustness to random loss • Tunable opportunistic friendliness • Streaming, multihop wireless, and forwarding at the Transport layer to receive attention and make good progress Proprietary Content

43. Steady State Characteristics (TCPW RE) For small loss rate, TCPW has much larger window than NewReno. More scalable! Proprietary Content

44. Fairness (TCPW RE) For small loss rate, TCPW is more fair than NewReno Proprietary Content