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End to End Routing Behavior in the Internet

End to End Routing Behavior in the Internet. Vern Paxson Network Research Group Lawrence Berkeley National Laboratory University of California, Berkeley. Presented by Shreeram Sahasrabudhe (sas4). Goal. Trying to answer questions like

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End to End Routing Behavior in the Internet

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  1. End to End Routing Behavior in the Internet Vern Paxson Network Research Group Lawrence Berkeley National Laboratory University of California, Berkeley Presented by Shreeram Sahasrabudhe (sas4)

  2. Goal • Trying to answer questions like • What sort of pathologies and failures occur in the Internet routing? • Do routes remain Stable over time or change frequently? • Do routes from A and B tend to be symmetric as routes from B to A? Framework 40000 end-to-end route measurements using repeated “traceroutes” between 37 Internet sites in 1994 & 1995

  3. Routing in the Internet • Internet: • Autonomous Systems (AS): collection of routers and hosts running a single Interior Gateway Protocol (IGP) • Administrative Domain: Routers and hosts are under a single administrative authority and a set of IGPs. • Border Gateway Protocol (BGP) allows arbitrary interconnection topologies between AS.

  4. Methodology • Apparatus: • Network Probe Daemon (NPD) run on a number of sites. • These NPDs were contacted at exponentially distributed intervals by a control program “npd_control”, to measure route to another NPD site using traceroute. • N2 scaling: if N sites then it can measure O(N2) internet paths between sites. • Two sets of measurements: D1 (Dec 1994; measurement time interval 1-2 days) and D2 (Dec 1995; 60% mean inter-measurement interval of 2 hours, 40% mean interval of about 2.75 days, paired measurements AB and BA ) • Why Exponential Sampling? • Corresponds to additive random sampling which samples all instantaneous signal values with equal probability. • Measurement times form a poisson process. Hence can apply Wolff’s PASTA principle. • How much representative of the real Internet? • Experiment routes cover more than half the AS by weight (prominence in internet routing). • Significant cross-section of internet behavior.

  5. Routing Pathologies • Routing Loops: • Forwarding loop; Information loop • traceroute loop (0.13% in D1, 0.16% D2) • Erroneous Routing: • Found 1 example CTIsraelUK! • Connectivity altered mid-stream • 0.16% D1 and 0.44% D2 • Fluttering • Rapidly oscillating routing • Infrastructure Failures • An inside router gives “host unreachable” message • Unreachable due to many hops • 6 from D2 measurements went beyond the traceroute’s limit of 30 • Mean path length: D1(15.6) and D2(16.2)

  6. Outages • Temporary outages • Sequence of consecutive traceroute packets are lost • 1 to 5 losses = D1(44%), D2(55%) • 6 or more = D1(0.96%), D2(2.2%) • For more than 6 losses (30 sec outage= 5sec X 6losses) • Time-of-day patterns • Temporary outage at least 30sec = 8% at 3-4pm • Infrastructure failure = 9.3% at 3-4pm and 7.6% at 6-7pm

  7. Prevalence of dominant route Routing Stability • Routing Prevalence Prevalence: A likelihood of currently observed router r being observed again in future Internet paths are strongly dominated by a single route, but there is also a significant site-to-site variation

  8. Routing Persistence Persistence: Given that we observed a router r at time t, how long before that route is likely to have changed. • More difficult to measure • Classification • Rapid route alternation: Observed measurements made <= 60 sec apart and <= 10min apart • Medium scale route alternation: Observed measurements <= 1 hour • Large-scale route alternation: <= 6 hrs • Long Lived Routes: Remaining (> 6hours) What is the chance of observing a route for at least a week= 90%

  9. Routing Symmetry • Affects: • One way propagation estimates (RTT/2) • Asymmetry complicates network measurement, trouble shooting, accounting and router’s flow calculation • Asymmetry complicates network troubleshooting • Analysis of routing symmetry • 49% of D2 measurements observed an asymmetric path between sites. • 30% of the paired measurements observed different autonomous systems in the virtual path’s two directions.

  10. Conclusions • The likelihood of encountering a major routing pathology more than doubled in a year from end of ‘94 to ’95. • Internet paths are heavily dominated by a single prevalent route, but the persistence varies from seconds to days • There is not typical internet path. Different sites or pairs of sites encounter very different routing characteristics. • Possible improvements to the methodology could be: • NPDs could be given more variety of measurement requests. • Use a more sophisticated tool than traceroute.

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