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Peering Benefits and the Long Tail

Peering Benefits and the Long Tail. Steven Wallace ssw@anml.iu.edu & David A. J. Ripley daripley@anml.iu.edu. What do we want to discover, and how?. Suppose we start peering with a given list of ASNs… That are all customers of a peering facility, for instance.

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Peering Benefits and the Long Tail

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  1. Peering Benefitsand the Long Tail Steven Wallace ssw@anml.iu.edu & David A. J. Ripley daripley@anml.iu.edu

  2. What do we want to discover, and how? • Suppose we start peering with a given list of ASNs… • That are all customers of a peering facility, for instance. • How much of our traffic is going to be routed through those ASNs? • Or a rough estimate, at least. • We’re going to need: • A breakdown of network traffic (e.g. from netflow) • All possible ways to get from one place to another • A list of the ASs that we’re interested in peering with.

  3. How many routes? • We need a “complete” view of the network. • RouteViews project @ University of Oregon (www.routeviews.org) • RIB dumps from Zebra BGPD at all RouteViews sites. • University of Oregon, Eugene Oregon USA • Equinix, Asburn VA USA • ISC (PAIX), Palo Alto CA USA • KIXP, Nairobi Kenya • LINX, London UK • DIXIE (NSPIXP) Tokyo Japan • 82 Unique ASs peering with RouteViews • Approximately 11 million routes, 192,000 prefixes.

  4. AS path pre-processing • We needed to do a little bit of tweaking to the AS paths to avoid problems later. • Adjacent duplicate ASNs are remove from all the paths. • (This is almost always when there’s been prepending.) • AS sets are split • This isn’t really the right thing, but it happens very rarely. • If a RouteViews peer is found in an AS path, everything to the left of it is removed.

  5. Traffic Volume • We used flow-tools (http://www.splintered.net/sw/flow-tools/) to generate per-host traffic totals. • ~3.5 months of data, July 7th -- September 20th 2006 from IU GigaPop • (Actually, they were /24’s) • There are about 5.4 million unique /24’s in our sample. • 31,004,709,978,854 bytes total traffic.

  6. Assign Traffic • Longest prefix match to calculate per-prefix traffic totals from per-host data. • Net::Patricia (http://net.doit.wisc.edu/~plonka/Net-Patricia/) • Consider all possible routes for every prefix. • The “AS of Interest” that “wins” that traffic is the one closest to the origin AS. • But no further than N hops from the origin. • In our case, N=1, but this is a knob we can turn. • In other words, traffic is assigned to a peering point customer that is either the origin of the traffic, or peers with the origin. • In the event of a tie, the first AS in the list wins.

  7. Results The top 10… doesn’t add up to much?

  8. Results

  9. How do we do it? • There is no secret sauce. • Some bash and perl scripts. • You could do it yourself • But you don’t have to! • It’s not perfect, but it (hopefully) is in the ballpark. • The most time consuming part is generating the report from the netflow data. • But you don’t have to use 3.5 months…

  10. Questions, comments? ssw@anml.iu.edu

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