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/

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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 - PowerPoint PPT Presentation

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Page 1: Internet Topology

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/

Page 2: Internet Topology

2

Returning the Midterm Exam

• Exam scoring break down–Range: 70-100–Average: 89–Median: 92

• See the course Web site–Exam–Answer key

Page 3: Internet Topology

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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

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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

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Autonomous System NumbersAS Numbers are 16 bit values.

• 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, …• …

Currently just over 20,000 in use.

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AS Topology

• Node: Autonomous System

• Edge: Two ASes that connect to each other

1

2

3

4

5

67

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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

AS 1

AS 2

d

Exchange Point

AS 1

AS 2

d

AS 3

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Interdomain Paths

1

2

3

4

5

67

ClientWeb server

Path: 6, 5, 4, 3, 2, 1

Page 9: Internet Topology

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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

Page 10: Internet Topology

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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

d

d

provider

customer

customer

provider

Traffic to the customer Traffic from the customer

advertisements

traffic

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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 $$$)

peerpeer

Traffic to/from the peer and its customers

d

advertisements

traffic

Page 12: Internet Topology

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Princeton Example

• Internet: customer of AT&T and USLEC

• Research universities/labs: customer of Internet2

• Local residences: peer with Patriot Media

• Local non-profits: provider for several non-profits

AT&T USLEC Internet2

Patriotpeer

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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

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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 A

Customer B

multiplepeeringpoints

Provider A

Provider B

Early-exit routing

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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

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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 10 100 1000

CC

DF

1

0.1

0.01

0.001

AS degree

All ASes have 1 or more neighbors

Very few have degree >= 100

Page 17: Internet Topology

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Characteristics of AS Paths

• AS path may be longer than shortest AS path

• Router path may be longer than shortest path

s d

3 AS hops, 7 router hops

2 AS hops, 8 router hops

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Intra-AS Topology

• Node: router

• Edge: link

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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

Page 20: Internet Topology

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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

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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 …

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Backbone Networks

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

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Abilene Internet2 Backbone

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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

Intra-PoP

Other networks

Inter-PoP

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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

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Customer Connecting to a Provider

Provider Provider

1 access link 2 access links

Provider

2 access routers

Provider

2 access PoPs

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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

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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

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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

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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

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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

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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

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Map Traceroute Hops to ASes

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

Traceroute output: (hop number, IP)AS25

AS25

AS25

AS25

AS11423

AS3356

AS3356

AS3356

AS3356

AS1668

AS1668

AS1668

AS5662

Berkeley

CNN

Calren

Level3

AOL

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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

AT&T Sprint

Harvard HarvardB-schoold1 d2

???

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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

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Paths You Should Never See (“Invalid”)

Customer-provider

Peer-peer

two peer edges

transit through a customer

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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

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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