Characterizing the Internet Hierarchy Characterizing the Internet Hierarchy from Multiple Vantage Pointsfrom Multiple Vantage Points

Jennifer RexfordInternet and Networking Systems

AT&T Labs - Research; Florham Park, NJ

http://www.research.att.com/~jrex

Work with L. Subramanian, S. Agarwal, and R. Katz http://www.cs.berkeley.edu/~sagarwal/research/BGP-hierarchy/

OutlineOutline Internet architecture

– Autonomous Systems (ASes) and IP addressing

– Interdomain routing and AS relationships

Type-of-relationship problem– Motivation, formulation, and practical challenges

Analyzing partial views of the AS graph– Assigning a rank to each AS from a single vantage point

– Comparing ranks of ASes across multiple vantage points Analysis results

– Interdomain routing data and inferred AS relationships

– Five-level classification of the Internet hierarchy

Conclusions

Internet ArchitectureInternet Architecture

Divided into Autonomous Systems– Distinct regions of administrative control (~14,000)

– Set of routers and 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 stub network run by a company or universityInteraction between Autonomous Systems

– Internal topology is not shared between ASes

– … but, neighboring ASes interact to coordinate routing

Autonomous Systems (ASes)Autonomous Systems (ASes)

1

2

3

4

5

67

Client (128.235.184.76)Web server

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

IP Addressing (for the host IP Addressing (for the host www.etri.re.krwww.etri.re.kr))

32 bits in dotted-quad notation (129.254.19.28)

Divided into network and host portions

129.254.0.0/16: 16-bit prefix with 232-16 addresses

10000001 11111110 00010011 00011100

Network (16 bits) Host (16 bits)

129 254 19 28

Border Gateway Protocol (BGP)Border Gateway Protocol (BGP)ASes exchange info about who they can reach

– IP prefix: block of destination IP addresses

– AS path: sequence of ASes along the path

Policies configured by the AS’s network operator– Path selection: which of the paths to use?

– Path export: which neighbors to tell?

3748 4766 7018

129.254.19.28

“I can reach 129.254.0.0/16”

“I can reach 129.254.0.0/16 via AS 4766”

ETRI

KIX AT&T

Customer-Provider RelationshipCustomer-Provider Relationship

Customer pays provider for access to the InternetAS exports customer’s routes to all neighborsAS exports provider’s routes only to its customers

d customer

provider

Traffic to the customer

d provider

customer

Traffic from the customer

advertisements

traffic

Peer-Peer RelationshipPeer-Peer Relationship

Peers exchange traffic between their customers Free of charge (assumption of even traffic load)AS exports a peer’s routes only to its customers

peerpeer

Traffic to/from the peer and its customers

d

advertisements

traffic

Moving Beyond the AS GraphMoving Beyond the AS Graph

AS graph doesn’t capture effects of routing policies– Some paths not allowed (e.g., transit through a peer)

– Local preference of paths (e.g., prefer customer path)

– Can’t simply compute shortest path on the graph

AS graph doesn’t capture the Internet hierarchy– Large AS may have few neighbors (mostly peers)

– Small AS may have many neighbors (mostly providers)

– Can’t simply rely on node degree to rank the nodes

Need to know the relationship between AS pairs

AS Relationships MatterAS Relationships Matter

Understanding the Internet’s basic structure– More than just a graph of interconnected ASes

Placement of servers for content distribution– Place replicas so they can reach everyone well

Selection of new peers or providers for an AS– Select peers/providers with good “reach” to others

Installing route filters to protect the network– Filter customer routes that include other large providers

Analyzing the convergence properties of BGP– Hierarchical relationships avoid protocol oscillation

Inferring Relationships from Routing DataInferring Relationships from Routing Data

Practical realities of the Internet– AS graph is not known

– AS relationships are proprietary

– … at least some routing data is publicly available!

Exploiting routing data– Available via traceroute experiments or BGP tables

– Provides a set of AS paths, such as “7018 4766 3748”

– Implies existence of edges (7018, 4766) & (4766, 3748)

– Implies that 4766 (KIX) allows AS 7018 (AT&T) to transit to AS 3748 (ETRI)

Valid and Invalid PathsValid and Invalid Paths

AS relationships limit the kinds of valid paths– Uphill portion: customer-provider relationships

– Plateau: zero or one peer-peer edge

– Downhill portion: provider-customer relationships

ValidInvalid

Invalid

Lixin Gao, “On inferring Autonomous System relationships in the Internet,” IEEE/ACM Transactions on Networking, December 2001.

Rutgers NJIT

QwestAT&T

AT&TSprint UUNET

AT&T UUNET

AT&T Research

Type-of-Relationship ProblemType-of-Relationship Problem

Given the inputs– AS graph G(V,E) with vertices V and edges E

– Set of paths P on the graph G

Find a solution that– Labels each edge with an AS relationship

– Minimizes the number of invalid paths in P

Properties of the problem– NP complete (?)

– May have multiple solutions

– We propose a heuristic algorithm

Practical ChallengesPractical Challenges

Peer-peer relationships are hard to infer– Mislabeling a peer-peer edge as provider-customer does not

change a valid path into an invalid path

– We use heuristics to detect the peer-peer edges

Some AS pairs have unusual relationships– Sibling ASes that provide transit service for each other

– Backup relationship for connectivity under failure

– Misconfiguration of a conventional AS relationship

– We detect these cases by analyzing the “invalid” paths

Getting access to a large path set P is hard– We exploit BGP routing tables from multiple vantage points

Validation ApproachesValidation Approaches

Quantify the number of invalid paths– Small number suggests better results

– …still, this doesn’t mean that inferences are correct

Compare results with other inference algorithms– Higher confidence if inferences are the same

– … still, both algorithms could give wrong answers

Compare results with Routing Arbiter Database– Higher confidence if consistent with RADB routing policies

– … still, RADB information is incomplete and out-of-date

Compare results with proprietary ISP data– Higher confidence if answers are correct for this AS– … still, answers may be wrong for other ASes

Partial View of the AS GraphPartial View of the AS Graph

Routing data from a single source AS– Collection of paths starting from the source

– Directed graph from union of all edges in these paths

Actual graph

A

B

C D

E

F

E

FD

C

B

A

B

AC

D

E

F

Assigning Rank to AS in a Partial ViewAssigning Rank to AS in a Partial View

Reverse pruning algorithm to assign rank– Rank 1 to the leaves, then remove leaves

– Rank 2 to the leaves, then remove leaves…

– Single (largest) rank to nodes in connected component, if any

E

FD

C

B

A

B

AC

D

E

F1

1 1

1

2

3

4

2

3

4

5 5

Combining Information From Multiple ViewsCombining Information From Multiple Views

Vector of ranks for each AS– A single element for each of the n views

Dominance: provider-customer relationship– Provider has higher ranks than customer in most views

– For example, B has (2,5) and A has (1,1) Equivalence: peer-peer relationship

– Peers have equal ranks in or inconsistent ranks

– For example, C has (3,4) and D has (4,3)Probabilistic inference

– Thresholds to tolerate some variations across the views

– E.g., an AS dominates in n-1 views and dominated in 1

Applying Our AlgorithmApplying Our Algorithm

Applying the algorithm to ten public BGP tables– RouteViews table and nine Looking Glass servers

– Extracted set of unique paths P for each view

– Applied reverse pruning algorithm to each view

– Applied inference rules to the vectors of ranks

Results of the analysis on data from April 2001– AS graph with 10,698 ASes and 23,935 edges

– Inferences were made for 99.2% of the edges

– 94.5% provider-customer and 4.7% peer-peer edges

– Most inferences do not require the probabilistic rules

Advantage of Multiple Vantage PointsAdvantage of Multiple Vantage Points

A single vantage point is not enough– 15% of the edges appear in exactly one BGP table

– Only 25% of the edges appear in all ten BGP tables

Analyzing Invalid PathsAnalyzing Invalid Paths

Checking the validity of inferences– Assume the relationship inferences are correct

– Identify paths that are invalid under these inferences

– Compute the number of invalid paths

– Investigate common anomaly triples (A, B, C)

Results of our analysis– Applied to paths in 2 of the original 10 BGP tables

– Applied to paths in 4 other BGP tables

– 0.5-3% of paths are invalid for five of the six tables

– 8.7% of paths are invalid for the KDDI table

Common Anomaly PatternsCommon Anomaly Patterns

Misconfiguration– (1, 65112, 6461): 65112 is a private AS that should not

appear between Genuity and AboveNet

Sibling relationships– (7018, 6841, 3300): Infonet Europe merged with AUCS

– (1239, 1740, 7018): Cerfnet was acquired by AT&T

– (1239, 8043, 6395): IXC Communications acquired SmartNAP and renamed Broadwing

Heuristic for identifying sibling relationships– AS pair that appears in a large number of “invalid” paths

– Our analysis identified 22 possible sibling relationships

AS ClassificationAS Classification

Directed AS graph– Directed edge from provider to customer

– Bidirectional edge between two peers

Lowest level: Stubs– Leaf nodes: no peers or downstream customers

– 8898 of the 10915 ASes (82.5% of ASes)

– Ex: UC Berkeley (25), AT&T Labs (6431), and ETRI (3748)

Next lowest level: Regional ISPs– Leaf nodes after successive pruning of leaf nodes

– 971 ASes of the 10915 ASes (8.9% of ASes)

– Ex: PacBell (5676), US West (6223), and UUNET Canada (815) Remaining 1046 ASes: Core

Dense CoreDense Core

Ways to classify so-called “tier-1” ASes– Any AS with no upstream provider (98 such nodes)

– AS set that forms the largest clique of peer edges (13 nodes)

Relaxing the definition– Tolerate some missing or misclassified edges

– Tolerate some ASes with sibling relationships

“Almost a clique”– Subgraph of m nodes with in and out degree at least m/2

– Greedy algorithm for locating the largest near-clique

20 ASes in the near-clique– 15 of the ASes form a subgraph just 3 edges short of a clique

– Genuity, Sprint, UUNET, AT&T, Verio, Level3, C&W,…

Transit and Outer CoreTransit and Outer Core

Transit core– ASes that peer with the dense core and each other

– Notion of a “weak in-way cut” to isolate these ASes

– Algorithm for identifying the ASes in transit core

– 129 ASes, including top providers in Europe and Asia

– Ex: UUNET Europe, KDDI, and Singapore Telecom

Outer core– All of the remaining ASes in the core

– 897 ASes, including large regional and national ISPs

– Ex: Turkish Telecom and Minnesota Regional Network

Node Degree is Not EnoughNode Degree is Not Enough

Node degree ignores relationships– A stub AS may have many upstream providers (one bankrupt!)

– A core AS may have a small # of peers (TeliaNet USA degree 40)

– Some ASes have customers that don’t have AS numbers

Related WorkRelated Work

AS graph characterization– Constructing graph from BGP tables or traceroute experiments

– Characterizing the topological properties of the graph

Inferring AS relationships (Lixin Gao)– Identifies the key properties of paths (uphill, downhill, etc.)

– Heuristic using node degree to infer boundary point between the uphill and downhill portions of the path

– Application of the algorithm using RouteViews routing table

Characterization of the hierarchy of ASes– Early work by Govindan/Reddy based on node degree

– Recent work by Ge et al based on AS relationships

ConclusionsConclusions

Inferring AS relationships– Reverse pruning to assign rank to each AS

– Comparison of ranks from different vantage points

Performance evaluation– Application of algorithm to collection of ten BGP tables

– Exploration of the anomalies that cause invalid paths

Characterization of Internet hierarchy– Stub, regional ISP, outer core, transit core, & dense core

– Algorithms for identifying the three parts of the core

– Application to AS graph inferred from the BGP tables

Ongoing WorkOngoing Work

Classification of siblings– Use anomalous triples (A, B, C) to identify siblings

– Group siblings into a single node (with union of edges)

– Repeat classification of the AS hierarchy on new graph

Longitudinal study– Repeat the study over a period of time with new data

– Study how AS relationships and hierarchy changes

Validation of our inference results– Compare to RADB, Lixin’s results, AT&T data, etc.

http://www.cs.berkeley.edu/~sagarwal/research/BGP-hierarchy/

Digression #1: Really Weird “Invalid” Paths…Digression #1: Really Weird “Invalid” Paths…

Properties of the path– Two tier-1 U.S. providers (Genuity and UUNet)

– One service provider in Hong Kong (Hutchinson)

– Another tier-1 U.S. provider (AT&T) at the end of the path Looking at internal AT&T configuration data…

– AT&T does not have a BGP session with AS 9304

– AT&T does not originate the prefixes (e.g., 152.141.116.0/24) Explanation

– Another AS was using the AT&T AS number (for over a year!)

– We sent them an e-mail and asked them to stop, and they did

1 701 703 9304 7018

Genuity UUNet Hutchinson AT&T

Digression #1: How Could This Happen, and Persist?Digression #1: How Could This Happen, and Persist?

BGP configuration is done locally by neighbors– Customer configures its router with AS number 7018

– Provider configures its router with neighbor of 7018 The misconfiguration didn’t necessarily cause a problem

– Hop-by-hop routing took the traffic to the right place

– Most BGP policies don’t look at the identity of the ASes Could have caused a problem: route filtering

– Large providers might applying filtering to customer routers

– Discard routes with other large providers in the path Could have caused a problem: loop detection

– The bogus routes did not appear in AT&T’s routing tables

– AT&T router saw 7018 in the path and discarded the route

– AT&T router did have a route for the supernet (152.141.0.0/16)

Digression #2: Making Up The ExamplesDigression #2: Making Up The Examples

Getting an IP address– E-mail from ansari@adm.njit.edu

– “nslookup adm.njit.edu” gave 128.235.184.176

Finding the AS number and a sample path– telnet://route-views.oregon-ix.net/

– “show ip bgp 128.235.184.176”

– One of the paths is “7018 209 4246”

Double checking this belongs to NJIT– “whois –h whois.arin.net 128.235.184.176”

– “whois –h whois.arin.net 4246”

Digression #2: whois –h whois.arin.net 128.235.184.76Digression #2: whois –h whois.arin.net 128.235.184.76

OrgName: New Jersey Institute of Technology

OrgID: NJIT

Address: 323 Martin Luther King Boulevard

City: Newark

StateProv: NJ

PostalCode: 07102

Country: US

NetRange: 128.235.0.0 - 128.235.255.255

CIDR: 128.235.0.0/16

NetName: NJIT

NetHandle: NET-128-235-0-0-1

Parent: NET-128-0-0-0-0

NetType: Direct Assignment

NameServer: DNS1.NJIT.EDU

NameServer: DNS2.NJIT.EDU

NameServer: THORIN.UTHSCSA.EDU

Comment:

RegDate:

Updated: 2001-04-05

TechHandle: PT35-ARIN

TechName: Teklinski, Peter

TechPhone: +1-973-596-2908

TechEmail: pt@njit.edu