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Internet Topology

Internet Topology. COS 461: Computer Networks Spring 2006 (MW 1:30-2:50 in Friend 109) Jennifer Rexford Teaching Assistant: Mike Wawrzoniak http://www.cs.princeton.edu/courses/archive/spring06/cos461/. Returning the Midterm Exam. Exam scoring break down Range: 70-100 Average: 89

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Internet Topology

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  1. Internet Topology COS 461: Computer Networks Spring 2006 (MW 1:30-2:50 in Friend 109) Jennifer Rexford Teaching Assistant: Mike Wawrzoniak http://www.cs.princeton.edu/courses/archive/spring06/cos461/

  2. Returning the Midterm Exam • Exam scoring break down • Range: 70-100 • Average: 89 • Median: 92 • See the course Web site • Exam • Answer key

  3. Goals of Today’s Lecture • Internet’s two-tiered topology • Autonomous Systems, and connections between them • Routers, and the links between them • AS-level topology • Autonomous System (AS) numbers • Business relationships between ASes • Router-level topology • Points of Presence (PoPs) • Backbone and enterprise network topologies • Inferring network topologies • By measuring paths from many vantage points

  4. Internet Routing Architecture • Divided into Autonomous Systems • Distinct regions of administrative control • Routers/links managed by a single “institution” • Service provider, company, university, … • Hierarchy of Autonomous Systems • Large, tier-1 provider with a nationwide backbone • Medium-sized regional provider with smaller backbone • Small network run by a single company or university • Interaction between Autonomous Systems • Internal topology is not shared between ASes • … but, neighboring ASes interact to coordinate routing

  5. Autonomous System Numbers AS Numbers are 16 bit values. Currently just over 20,000 in use. • Level 3: 1 • MIT: 3 • Harvard: 11 • Yale: 29 • Princeton: 88 • AT&T: 7018, 6341, 5074, … • UUNET: 701, 702, 284, 12199, … • Sprint: 1239, 1240, 6211, 6242, … • …

  6. 4 3 5 2 6 7 1 AS Topology • Node: Autonomous System • Edge: Two ASes that connect to each other

  7. What is an Edge, Really? • Edge in the AS graph • At least one connection between two ASes • Some destinations reached from one AS via the other d d AS 1 AS 1 Exchange Point AS 2 AS 2 AS 3

  8. Interdomain Paths Path: 6, 5, 4, 3, 2, 1 4 3 5 2 6 7 1 Web server Client

  9. Business Relationships • Neighboring ASes have business contracts • How much traffic to carry • Which destinations to reach • How much money to pay • Common business relationships • Customer-provider • E.g., Princeton is a customer of AT&T • E.g., MIT is a customer of Level 3 • Peer-peer • E.g., Princeton is a peer of Patriot Media • E.g., AT&T is a peer of Sprint

  10. advertisements traffic Customer-Provider Relationship • Customer needs to be reachable from everyone • Provider tells all neighbors how to reach the customer • Customer does not want to provide transit service • Customer does not let its providers route through it Traffic to the customer Traffic from the customer d provider provider customer d customer

  11. advertisements traffic Peer-Peer Relationship • Peers exchange traffic between customers • AS exports only customer routes to a peer • AS exports a peer’s routes only to its customers • Often the relationship is settlement-free (i.e., no $$$) Traffic to/from the peer and its customers peer peer d

  12. Princeton Example • Internet: customer ofAT&T and USLEC • Research universities/labs: customer ofInternet2 • Local residences: peer with Patriot Media • Local non-profits: provider for several non-profits AT&T Internet2 USLEC Patriot peer

  13. AS Structure: Tier-1 Providers • Tier-1 provider • Has no upstream provider of its own • Typically has a national or international backbone • UUNET, Sprint, AT&T, Level 3, … • Top of the Internet hierarchy of 12-20 ASes • Full peer-peer connections between tier-1 providers

  14. Efficient Early-Exit Routing • Diverse peering locations • Both costs, and middle • Comparable capacity at all peering points • Can handle even load • Consistent routes • Same destinations advertised at all points • Same AS path length for a destination at all points Customer B Provider B multiple peering points Early-exit routing Provider A Customer A

  15. AS Structure: Other ASes • Tier-2 providers • Provide transit service to downstream customers • … but, need at least one provider of their own • Typically have national or regional scope • E.g., Minnesota Regional Network • Includes a few thousand of the ASes • Stub ASes • Do not provide transit service to others • Connect to one or more upstream providers • Includes vast majority (e.g., 85-90%) of the ASes

  16. Very few have degree >= 100 Characteristics of the AS Graph • AS graph structure • High variability in node degree (“power law”) • A few very highly-connected ASes • Many ASes have only a few connections 1 All ASes have 1 or more neighbors 0.1 CCDF 0.01 0.001 AS degree 1 10 100 1000

  17. Characteristics of AS Paths • AS path may be longer than shortest AS path • Router path may be longer than shortest path 2 AS hops, 8 router hops d s 3 AS hops, 7 router hops

  18. Intra-AS Topology • Node: router • Edge: link

  19. Hub-and-Spoke Topology • Single hub node • Common in enterprise networks • Main location and satellite sites • Simple design and trivial routing • Problems • Single point of failure • Bandwidth limitations • High delay between sites • Costs to backhaul to hub

  20. Princeton Example • Hub-and-spoke • Four hub routers and many spokes • Hub routers • Outside world (e.g., AT&T, USLEC, …) • Dorms • Academic and administrative buildings • Servers

  21. Simple Alternatives to Hub-and-Spoke • Dual hub-and-spoke • Higher reliability • Higher cost • Good building block • Levels of hierarchy • Reduce backhaul cost • Aggregate the bandwidth • Shorter site-to-site delay …

  22. Backbone Networks • Backbone networks • Multiple Points-of-Presence (PoPs) • Lots of communication between PoPs • Accommodate traffic demands and limit delay

  23. Abilene Internet2 Backbone

  24. Points-of-Presence (PoPs) • Inter-PoP links • Long distances • High bandwidth • Intra-PoP links • Short cables between racks or floors • Aggregated bandwidth • Links to other networks • Wide range of media and bandwidth Inter-PoP Intra-PoP Other networks

  25. Where to Locate Nodes and Links • Placing Points-of-Presence (PoPs) • Large population of potential customers • Other providers or exchange points • Cost and availability of real-estate • Mostly in major metropolitan areas • Placing links between PoPs • Already fiber in the ground • Needed to limit propagation delay • Needed to handle the traffic load

  26. Customer Connecting to a Provider Provider Provider 2 access links 1 access link Provider Provider 2 access PoPs 2 access routers

  27. Multi-Homing: Two or More Providers • Motivations for multi-homing • Extra reliability, survive single ISP failure • Financial leverage through competition • Better performance by selecting better path • Gaming the 95th-percentile billing model Provider 1 Provider 2

  28. Shared Risks • Co-location facilities (“co-lo hotels”) • Places ISPs meet to connect to each other • … and co-locate their routers, and share space & power • E.g., 32 Avenue of the Americas in NYC • Shared links • Fiber is sometimes leased by one institution to another • Multiple fibers run through the same conduits • … and run through the same tunnels, bridges, etc. • Difficult to identify and accounts for these risks • Not visible in network-layer measurements • E.g., traceroute does not tell you links in the same ditch

  29. Learning the Internet Topology • Internet does not have any central management • No public record of the AS-level topology • No public record of the intra-AS topologies • Some public topologies are available • Maps on public Web sites • E.g., Abilene Internet2 backbone • Otherwise, you have to infer the topology • Measure many paths from many vantage points • Extract the nodes and edges from the paths • Infer the relationships between neighboring ASes

  30. Inferring an Intra-AS Topology • Run traceroute from many vantage points • Learn the paths running through an AS • Extract the hops within the AS of interest 1 169.229.62.1 2 169.229.59.225 3 128.32.255.169 4 128.32.0.249 5 128.32.0.66 6 209.247.159.109 7 209.247.9.170 8 66.185.138.33 9 66.185.142.97 10 66.185.136.17 11 64.236.16.52 inr-daedalus-0.CS.Berkeley.EDU soda-cr-1-1-soda-br-6-2 vlan242.inr-202-doecev.Berkeley.EDU gigE6-0-0.inr-666-doecev.Berkeley.EDU qsv-juniper--ucb-gw.calren2.net POS1-0.hsipaccess1.SanJose1.Level3.net pos8-0.hsa2.Atlanta2.Level3.net pop2-atm-P0-2.atdn.net Pop1-atl-P3-0.atdn.net pop1-atl-P4-0.atdn.net www4.cnn.com AOL

  31. Challenges of Intra-AS Mapping • Firewalls at the network edge • Cannot typically map inside another stub AS • … because the probe packets will be blocked by firewall • So, typically used only to study service providers • Identifying the hops within a particular AS • Relies on addressing and DNS naming conventions • Difficult to identify the boundaries between ASes • Seeing enough of the edges • Need to measure from a large number of vantage points • And, hope that the topology and routing doesn’t change

  32. Inferring the AS-Level Topology • Collect AS paths from many vantage points • Learn a large number of AS paths • Extract the nodes and the edges from the path • Example: AS path “1 7018 88” implies • Nodes: 1, 7018, and 88 • Edges: (1, 7018) and (7018, 88) • Ways to collect AS paths from many places • Mapping traceroute data to the AS level • Measurements of the interdomain routing protocol

  33. AS25 AS25 AS25 AS25 AS11423 AS3356 AS3356 AS3356 AS3356 AS1668 AS1668 AS1668 AS5662 Berkeley Calren Level3 AOL CNN Map Traceroute Hops to ASes Traceroute output: (hop number, IP) 1 169.229.62.1 2 169.229.59.225 3 128.32.255.169 4 128.32.0.249 5 128.32.0.66 6 209.247.159.109 7 * 8 64.159.1.46 9 209.247.9.170 10 66.185.138.33 11 * 12 66.185.136.17 13 64.236.16.52

  34. d2 d1 Challenges of Inter-AS Mapping • Mapping traceroute hops to ASes is hard • Need an accurate registry of IP address ownership • Whois data are notoriously out of date • Collecting diverse interdomain data is hard • Public repositories like RouteViews and RIPE-RIS • Covers hundreds to thousands of vantage points • Especially hard to see peer-peer edges Sprint AT&T ??? Harvard B-school Harvard

  35. Inferring AS Relationships • Key idea • The business relationships determine the routing policies • The routing policies determine the paths that are chosen • So, look at the chosen paths and infer the policies • Example: AS path “1 7018 88” implies • AS 7018 allows AS 1 to reach AS 88 • AT&T allows Level 3 to reach Princeton • Each “triple” tells something about transit service • Collect and analyze AS path data • Identify which ASes can transit through the other • … and which other ASes they are able to reach this way

  36. two peer edges transit through a customer Paths You Should Never See (“Invalid”) Customer-provider Peer-peer

  37. Challenges of Relationship Inference • Incomplete measurement data • Hard to get a complete view of the AS graph • Especially hard to see peer-peer edges low in hierarchy • Real relationships are sometime more complex • Peer is one part of the world, customer in another • Other kinds of relationships (e.g., backup and sibling) • Special relationships for certain destination prefixes • Still, inference work has proven very useful • Qualitative view of Internet topology and relationships

  38. Conclusions • Two-tiered Internet topology • AS-level topology • Intra-AS topology • Inferring network topologies • By measuring paths from many vantage points • Next class • Vivek Pai guest lecture • See reading assignment on the course Web site • Mike Wawrzoniak talking about assignment #2 • Start the assignment so you can ask questions • Next week • Intradomain and interdomain routing

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