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Monitoring Persistently Congested Internet Links

This study introduces new probing methods to enhance observability of core congestion in persistently congested internet links. The Pong tool specializes in measuring non-edge links with repetitive congestion, revealing systematic network issues. Lightweight and scalable, it serves as a foundation for a large-scale triggered monitoring system. Through coordinated probing and analyzing queuing delays, the methodology uncovers congestion patterns and offers insights into network topologies. The research focuses on improving measurement accuracy and adaptively selecting probing techniques based on quality of measurability. The tool aims to optimize internet monitoring, minimize errors, and detect anomalies effectively.

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Monitoring Persistently Congested Internet Links

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  1. Monitoring PersistentlyCongestedInternet Links Leiwen (Karl) Deng Aleksandar Kuzmanovic Northwestern University http://networks.cs.northwestern.edu

  2. Objective • New probing methods that can improve measurement observability for core congestion • Pong – a tool specialized in measuring a subset of non-edge links exhibiting repetitive congestion • Can reveal systematic problems such as routing pathologies, poorly-engineered network policies, or non-cooperative inter-AS relationships • Lightweight: monitoring in addition to on-demand measuring • A building block of a large scale triggered monitoring system for Internet congestion

  3. Repetitive Congestion • We focus on locating and monitoring non-edge links that exhibit repetitive congestion • Queuing delay as congestion indicator • Queue building-up repetitively happens on time scales ofone or more minutes.

  4. Methodology Highlights • Coordinated probing • Probe from both endpoints of a path • Combine end-to-end probes with (TTL limited) probes to intermediate routers • Infer underlying path topology conditions • Implicit inference • Based on measured queuing delays on different probing paths • Use statistics over longer time scales • Quantify measurement accuracy • Link measurability score

  5. f s d b Coordinated Probing Probe S D f (“forward”) probe b (“backward”) probe , , s (“source”) probe d (“destination”) probe , A Simplified Case – Symmetric Path

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

  7. f s d b Infer Underlying Path Topology Conditions Probe Δf Δd S D Δs Δb Condition: Δf +Δb ≈Δs +Δd Path Pattern: 4-p probing scenario

  8. Probe Probe Probe f f Pair up Pair up s s Congestion Congestion D S D S d d Observed by b probe only b Paired d probe b Paired d probe 4-p probing Fsd probing f s Congestion 4-p probing Δf +Δb ≈Δs +Δd D S Fsd probing Δf ≈Δs +Δd Fsb probing Δs ≈Δf +Δb b No suitable d probes to pair up with this s probe 2-p probing unconditional Estimates of half-path queuing delay Fsb probing Infer Underlying Path Topology Conditions Probing technique Condition Δfs Δfd

  9. |(Δf +Δb) − (Δs +Δd)| QoM4p = 1 − max(Δf +Δb, Δs +Δd) Demote |(Δf − (Δs +Δd)| Promote QoMfsd = 1 − max(Δf, Δs +Δd) |(Δs − (Δf +Δb)| QoMfsb = 1 − max(Δs, Δf +Δb) Select Probing Techniques Adjust probing technique online based on quality of measurability (QoM) Definition of QoM Condition Probing technique 4-p probing Fsd probing Fsb probing 2-p probing Δf +Δb ≈Δs +Δd Δf ≈Δs +Δd Δs ≈Δf +Δb unconditional (Last resort)

  10. Probe Probe Probe Probe Probe Δfd Δfs Δfs Δfd Δfs Δfd Δfd Δfs Δfd Δfs Locating Congested Links Perform coordinated probing for all intermediate nodes S D Probe all nodes simultaneously

  11. Probe Probe Congestion Congested link is identified Locating Congested Links Switch Point Approach S D Correlate probes to neighboring nodes

  12. Congestion f f f f f f f f f f f f f f f Tracing Congestion Status S D Link C (Identified congested link) Congestion Status Link C Time Use fast rate end-to-end probing

  13. 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 0.47s on/off 0.83s on/off Emulab Experiment Example Topology: 12 nodes (PCs), 11 links Link: 100Mbps, 2ms Cross traffic: Each consists of 3 parallel TCP flows, 50% time on and 50% time off. Build multiple bottlenecks: Cross traffics are added to corresponding links concurrently.

  14. 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 Emulab Experiment Example At the Beginning

  15. 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 0.47s on/off 0.83s on/off Emulab Experiment Example After adding backward bottlenecks

  16. 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 Emulab Experiment Example After adding two more forward bottlenecks

  17. Optimizing Pong in the Internet • Set queuing delay threshold • Based on distribution of queuing delay samples • Tune other parameters based on experiments on the PlanetLab • Minimize measurement errors • Detect and react to anomalies (clock skews, router alterations, ICMP queuing, etc) • Use instantaneous quality of measurement value as sample weight • Quantify measurement quality • Help select vantage points

  18. Quantify Measurement Quality • Help select vantage points • Link measurability score • Probing technique and quality of measurability • Queuing delay threshold quality • Observability score • Congestion observed on a less frequently congested link can be blurred by a much more frequently congested link on the same path.

  19. Conclusion • Pong – a tool specialized in measuring a subset of non-edge links exhibiting repetitive congestion • Coordinated probing • Infer underlying path topology conditions • Select probing techniques online • Quality of measurability • Quantify measurement quality • Link measurability score

  20. Thank you! Questions?

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