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From TCP to Net Neutrality and Back

This talk discusses TCP congestion control, the reusing of CDN measurements, and the importance of net neutrality in today's Internet. It explores non-incremental advances in TCP congestion control and the possibility of drafting behind CDNs for network measurements. Lastly, it addresses the ongoing debate on net neutrality and the potential impact on networking research and future strategies.

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From TCP to Net Neutrality and Back

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  1. From TCP to Net Neutrality and Back Aleksandar Kuzmanovic EECS Department Northwestern University http://networks.cs.northwestern.edu

  2. Today’s Talk • TCP congestion control • Reusing CDNs’ measurements • Net neutrality

  3. TCP Congestion Control • Question • Why do we care about TCP congestion control in the year 2007? • Overwhelming opinion: • TCP research is incremental • Not relevant any more • It is boring • No high-impact breakthroughs are possible any more

  4. Non-Incremental Advances are Possible • A. Kuzmanovic, “The Power of Explicit Congestion Notification,” in ACM SIGCOMM 2005. “… throughput increases by more than 40% while the average web response time simultaneously decreases by nearly an order of magnitude.” Server • A. Kuzmanovic, S. Floyd, and K. K. Ramakrishnan “Adding Explicit Congestion Notification (ECN) to TCP’s SYN/ACK Packets,” IETF Draft, work in progress.

  5. TCP Congestion Control • Slow-start phase • Double the sending ...... rate each round-trip ... time • Reach high throughput ...quickly

  6. TCP Congestion Control • Additive Increase –...Multiplicative Decrease • Fairness among flows

  7. TCP Congestion Control • Exponential • .backoff • System stability

  8. Breakthroughs are Possible • Exponential backoff • fundamentally wrong! • A. Mondal and A. Kuzmanovic, “Removing Exponential Backoff from TCP,” work in progress.

  9. Today’s Talk • TCP congestion control • Reusing CDNs’ measurements • Net neutrality

  10. Drafting Behind Akamai • Fact • CDNs (e.g., Akamai) perform extensive network and server measurements • Publish the results through DNS over short time scales • Can overlay networks reuse measurements collected by production CDNs? • Significantly reduce the amount of measurements (a complementary service) • No new infrastructure need to be deployed • Inherit the robustness of DNS • Easy integration with existing systems

  11. …….. En E2 E1 S A1 An A2 D DNS Server CDN-Driven One-Hop Source Routing

  12. Results • Key findings • DNS redirections sufficiently small • Strong correlation to network conditions • 50% of nodes “discovered” by Akamai outperform direct paths • Global Internet “weather-report” service for little to no cost • About impact • Akamai never liked the idea… • A-J. Su, D. Choffnes, A. Kuzmanovic, and F. Bustamante “Drafting Behind Akamai (Travelocity-Based Detouring),” in ACM SIGCOMM 2006.

  13. Relative Network Positioning via CDN Redirections • Wide-area distributed network systems can benefit from network positioning systems • P2p data sharing, multi-cast, online games • Relative network position is sufficient for most applications • Relative order is more important than absolute distance

  14. Redirection frequency for node A to replica server y Redirection frequency vectorfor node A Closest Node Selection cos_sim(A,B) < cos_sim(A,C) => dA,B > dA,C

  15. Rank Comparison 25% CRP Top1 closely matches Meridian 20% CRP Top5 outperforms Meridian

  16. Latency Analysis 80% of CRP Top 5 Error < 50ms 50% of CRP Top 5 Error < 25ms

  17. Clustering No common replica server between 2 clusters Node {D, E, F} redirect to common replica X

  18. Central Leader Election Node B has the largest sum of cosine similarity

  19. Today’s Talk • TCP congestion control • Reusing CDNs’ measurements • Net Neutrality

  20. Net Neutrality • Pro net neutrality: • www.savetheinternet.com • http://www.youtube.com/watch?v=v4cYuinTGWA • Anti net neutrality: • http://www.handsoff.org/blog/

  21. What is this all about? Google, Skype Microsoft, Yahoo, etc. AT&T

  22. ISP 1 ISP 2 ISP 3 Net Neutrality: Reality • ISPs deny service to VoIP flows • All networks with sufficient marketing power apply similar methods • The problem is moving deeper into the Internet core • The same is happening to p2p, gaming, and streaming services • Not just about discrimination: • Entire policies may be tuned in a biased way

  23. Networking Research • Give peace a chance! • How can ISPs cooperate for their mutual benefits? • How can endpoints optimize their local behavior while maximizing network performance? • How can we provide incentives for cooperation in other networking domains? • But what are we going to do if there will be no peace soon?

  24. Our Approach • Internet Audit: • A distributed system to enable network accountability: • What happened, where did it happen, and who is responsible? • Challenges: • Non-repudiatiable identification of discriminating network elements • Detect unfair service favoring, e.g., content provider/ISP alliances • Explore a range of threat models • from open DoS attacks to using network policies in destructive ways

  25. Preliminary Results • Problem: • Detect precise locations where queuing happens • A key building block in detecting discriminating jitter-boxes • Useful to know in general: • Overlay design (route around such spots) • Advanced congestion control • Fault diagnosis S D

  26. f s d b Coordinated Probing Probe S D f probe b probe , s probe d probe , , 4-p probing: a symmetric path scenario

  27. f s d b Locating Congestion Points Tracing Congestion Status Half-path queuing delay Coordinated Probing Probe Δf Δd S D Δs Δb Δfs Δfd

  28. Methodology Highlights • Coordinated probing • Send 4, 3, or 2 packets from two endpoints • Quality of Measurability (QoM) • Able to deterministically detect its own inaccuracy • Self-adaptivity • Switch among different probing schemes based on QoM and path properties

  29. 5 6 7 3 4 9 10 11 8 2 1 9 3 8 12 4 10 11 5 7 6 1 2 0.53s on/off 0.37s on/off 0.71s on/off 0.29s on/off 0.63s on/off Evaluation After adding two more forward bottlenecks

  30. Results • Edge vs. core • Edge more frequently congested than the core: 4.5 times on average • Intra-AS vs. Inter-AS • Edge: Intra-AS > Inter-AS • Core: Intra-AS < Inter-AS • Time domain • Edges: congestion events clustered in time • Core: congestion events dispersed in time • Links vs. Paths • Links: 12% congested, 3% considerably • Paths: 20% considerably congested

  31. Multiple Congested Points • Probability to observe multiple congested points on an end-to-end path • Grows as a power function of interval length • Decays exponentially with the number of congested points

  32. Summary http://networks.cs.northwestern.edu • Congestion control • Reusing CDNs’ redirections • Net neutrality and congestion measurements (Ericsson, Cisco) Other projects • Online traffic classification and profiling (Narus) • Monitoring p2p misconfigurations

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