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Characterizing the Internet Hierarchy from Multiple Vantage Points. Jennifer Rexford Internet and Networking Systems AT&T Labs - Research; Florham Park, NJ http://www.research.att.com/~jrex.

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characterizing the internet hierarchy from multiple vantage points

Characterizing the Internet Hierarchy from Multiple Vantage Points

Jennifer Rexford

Internet 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/

outline
Outline
  • Internet architecture
    • ASes, IP addressing, BGP 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
    • BGP routing data and inferred AS relationships
    • AS paths that are inconsistent with the inferences
    • Five-level classification of the Internet hierarchy
  • Conclusions
internet architecture
Internet Architecture
  • Divided into Autonomous Systems
    • Distinct regions of administrative control (~11,000)
    • 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 university
  • Interaction between Autonomous Systems
    • Internal topology is not shared between ASes
    • … but, neighboring ASes interact to coordinate routing
autonomous systems ases
Autonomous Systems (ASes)

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

4

3

5

2

6

7

1

Web server

Client

ip addressing and prefixes

00001100

00100010

10011110

00000101

IP Addressing and Prefixes
  • 32 bits in dotted-quad notation (12.34.158.5)
  • Divided into network and host portions
  • 12.34.158.0/23 is a 23-bit prefix with 29 addresses

12

34

158

5

Network (23 bits)

Host (9 bits)

interdomain routing with bgp between ases
Interdomain Routing with BGP (Between ASes)
  • ASes announce info about prefixes they can reach
  • Local policies for path selection (which to use?)
  • Local policies for route propagation (who to tell?)
  • Policies configured by the AS’s network operator

“I can reach 12.34.158.0/23

via AS 1”

“I can reach 12.34.158.0/23”

2

3

1

12.34.158.5

customer provider relationship

Traffic from the customer

provider

d

traffic

customer

Customer-Provider Relationship
  • Customer pays provider for access to the Internet
  • AS exports customer’s routes to all neighbors
  • AS exports provider’s routes only to its customers

Traffic to the customer

advertisements

provider

d

customer

peer peer relationship

traffic

Peer-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

Traffic to/from the peer and its customers

advertisements

peer

peer

d

as relationships matter
AS Relationships Matter
  • Motivating problems
    • Placement of servers for content distribution network
    • Selection of new peers or providers for an AS
    • Analyzing the convergence properties of the BGP protocol
    • Installing route filters to protect against misconfiguration
    • Understanding of the basic structure of the Internet
  • Knowing the AS graph is not enough
    • Interdomain routing is not shortest-path routing
    • Some paths not allowed (e.g., transit through a peer)
    • Local preference of paths (e.g., prefer customer path)
    • Node degree does not define the Internet hierarchy
  • Need to know the relationship between AS pairs
inferring relationships from routing data
Inferring 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 “701 7018 46”
    • Implies existence of edges (701, 7018) and (7018, 46)
    • Implies that 7018 (AT&T) allows AS 701 (UUNet) to transit to AS 46 (Rutgers)
valid and invalid paths
Valid 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

Valid

Invalid

Invalid

Lixin Gao, “On inferring Autonomous System relationships in the

Internet,” IEEE/ACM Transactions on Networking, December 2001.

type of relationship problem
Type-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 challenges
Practical 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 approaches
Validation 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 graph

D

C

C

C

D

D

E

E

E

B

B

F

A

A

A

F

F

Partial 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

B

Actual graph

assigning rank to as in a partial view

C

D

D

C

E

E

B

F

A

F

A

Assigning 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

B

5

5

1

1

4

4

3

3

2

2

1

1

combining information from multiple views
Combining 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 algorithm
Applying 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 points
Advantage 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 paths
Analyzing 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 patterns
Common 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
digression really weird invalid paths

1 701 703 9304 7018

Genuity

Hutchinson

UUNet

AT&T

Digression: 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
digression how could this happen and persist
Digression: 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)
as classification
AS 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 INRIA (1300)
  • 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 core
Dense 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 core
Transit 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 enough
Node Degree is Not Enough
  • Node degree ignores relationships
    • A stub AS may have many upstream providers
    • A core AS may have a small number of peers
    • Some ASes have customers that don’t have AS numbers
related work
Related 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
conclusions
Conclusions
  • 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 work
Ongoing 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/
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