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Passive Inference of Path Correlation

Investigate approaches for passive measurement of TCP throughput to determine the level of shared congestion. The study does not send any probe traffic but passively gathers information to learn. It is intended for use with long-lived, high-bandwidth applications.

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Passive Inference of Path Correlation

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  1. Passive Inference of Path Correlation Lili Wang, James N. Griffioen, Kenneth L. Calvert, Sherlia Shi Laboratory for Advanced Networking University of Kentucky CPSC538A course presentation Presented by : Lin Zhong

  2. Introduction • Investigate approaches based on passive measurement of TCP throughput to determine the level of shared congestion. -does not send any probe traffic, passively gathers information, and learn. -intended for use with long-lived , high- bandwidth applications.

  3. Related Work • Multipath routing techniques (RON) • Multiple paths from multiple replicated sources to increase (MDC, Erasure codes) • Integrate congestion control across multiple concurrent flows. (Modify TCP, maintain network congestion and schedule data transmission.) • Detect shared congestion (packet-pair, active probe)

  4. Capacity Conservation (ALG1) 1.reduces the rate of one of the flows by a known amount for a fixed time period (i.e., we turn the flow off) and then later returns the flow to its normal rate (i.e., we turn the flow back on). 2.looks for proportional changes in the bandwidth of the other flow(s). 3.If a change is consistent with other flow’s modulation, we assume the flows share a bottleneck; otherwise we assume they take independent paths.

  5. Emulab Experiement

  6. Limitation of Alg1 • when the background traffic changes frequently, • when the total number of flows sharing the bottleneck is large. • there are also many situations where the level of background traffic is constantly changing.

  7. Correlated Variation (ALG2) Basic idea: random background traffic will cause random changes to the foreground flows. Correlation coefficent :

  8. Computing the Correlation Lazy-evaluation approach • Nodes exchange their available bandwidth number • Candidate paths through the overlay are selected • Only measure the links which we concern their correlation • Record the path correlation information for future path selection.

  9. Conclusion • Proposed two techniques to detect path correlation - Observe the throughput change of one flow when other flow starts or finishing sending. (background traffic is fairly constantly) • Apply statistic technique to infer path correlation (background traffic is changing randomly) • Assume busy sources

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