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Merging Logical Topologies Using End-to-end Measurements

Merging Logical Topologies Using End-to-end Measurements. Michael Rabbat Mark Coates Robert Nowak. Internet Measurement Conference 2003 Tuesday October 28, 2003. A. 1. 2. 3. 4. 5. Topology Identification via Active Probing. Motivation: BGP data gives the big picture

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Merging Logical Topologies Using End-to-end Measurements

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  1. Merging Logical Topologies UsingEnd-to-end Measurements Michael Rabbat Mark Coates Robert Nowak Internet Measurement Conference 2003 Tuesday October 28, 2003

  2. A 1 2 3 4 5 Topology Identification via Active Probing Motivation: • BGP data gives the big picture • ICMP-based techniques (i.e. traceroute) don’t work everywhere Existing end-to-end techniques: • Single active source, many receivers • Assume tree structured logical topology • Exploit: • Correlated events on upstream links • Additive, non-decreasing nature of performance parameters [Ratnasamy & McCanne], [Duffield et al.], [Bestavros et al.], [Coates et al.]

  3. A 1 2 3 4 5 B 1 2 3 4 5 Extending to Multiple Sources • Marginal Utility [Barford et al., ‘01] • Can gain by using a few more sources • Net. Tomo. on General Topologies [Bu et al., ’02] • Evaluate various algorithms for inferring internal characteristics • Sources make measurements separately • Identifiability conditions given the general topology No labels on internal nodes  Merging is non-trivial

  4. A B A 1 2 3 4 5 B 1 2 3 4 5 3 2 4 5 1 Merging Strategy • Identify joining nodes merge topologies • Placement is logical, relative • Non-shared joining node • Merging node for routes to a single receiver • Shared joining node • Routes to multiple receivers merge at one node

  5. A A B B A B 1 1 2 2 1 1 2 2 Goal: Identify Shared Joining Nodes • Two sources, two receivers • Is there a shared joining node? • Locate joining node relative to branching node • All other cases have more than one non-shared joining node • Make measurements and form a binary hypothesis test: H0 : One joining node H1 : More than one joining node

  6. A B t(n) + t t t(n) v(n) 1 2 Packet Arrival Order Measurements • Procedure: • At t(n), send packets to Rcv1 • After t, send packets to Rcv2t > O(1/bmin) • Compare arrival orders • Repeat, varying send time at Bv(n) ~ Unif orm(-D, D)|D| ¼O(RTTmax) À t • Assumptions: • Sources synchronized (for now) • Arrival order determined at first shared queue t

  7. A B 1 Analysis: Packet Arrival Order and Timing

  8. A B Contours of p(d1, d2) d2 1 d1 2 Prob. different arrival order | v(n) Conditions for a Different Arrival Order

  9. Contours of p(d1, d2) d2 A B d1 1 2 Prob. different arrival order | v(n) For Non-Shared Topologies • On packet reordering [Bellardo & Savage, ’02] • Pr{In-network reordering} / 1/(time-spacing) • Sources of measurement noise • Packet reordering for a few values of v(n) • Spacing t distorted by queueing (also, for few values of v)

  10. A B t t(n) v(n) 1 2 Measure the Noise • Similar procedure: • At t(n), send packets to Rcv1 • After t, send to Rcv1 againt¼O(1/bmin) • Compare arrival orders • Repeat, varying send time at Bv(n) ~ Unif orm(-D, D)|D| ¼O(RTTmax) Send all packets to one receiver  Force one joining node 2 2 t 1 1 Must be noise 1 2 1 2

  11. A A B B 1 1 2 2 Making A Decision

  12. Rice ECE LAN 18 Unix/Linux hosts Spread across two buildings, two VLANs Mostly layer-2, two routers Validated with help from IT Internet “Test bed” 11 academic hosts Mostly N. American, few in Europe Validated using traceroute Extremely successful Some Experiments

  13. Summary • Merge logical topologies by identifying joining nodes • Shared joining nodes located relative to branching node • Novel multiple source active probing scheme • Uniform random offset • Look for packet arrival order differences • A few concluding remarks • Unicast or multicast • O(NS2 R2) measurements, reduce to O(NS2 R) using “stripes” • Infrastructure independent (layer-3 or layer-2) Signal Processing In Networking http://spin.rice.edu rabbat@cae.wisc.edu

  14. Probing from Multiple Sources A A B 2 1 1 Exploit correlation onupstream link, non-decreasing additive property of metrics Not as easy to exploit correlationon downstream link…

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