BGP and inter-AS economic relationships
E. Gregori1 , A. Improta2,1 , L. Lenzini2 , L. Rossi1 , L. Sani3
1
Institute of Informatics and Telematics, Italian National Research Council Pisa,
Italy
2
Information Engineering Department, University of Pisa, Italy
3
IMT Lucca, Institute for Advanced Studies, Lucca, Italy
Tuesday, May 10 - 2011
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
1 / 18
Paper goal
Development of an algorithm to infer economic relationships
among ASes composing the Internet, that takes heavily into
account the characteristics of exploited input data
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
2 / 18
Outline
1
Introduction and basilar concepts from previous works
2
Time-based tagging algorithm
3
Tagged topology analysis
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
3 / 18
Internet AS level topology
Internet: the largest collection of connected IP networks,
belonging to various organizations (e.g. Universities, ISP,
CDN)
A group of network under the same organization running a the
same routing protocol is an Autonomous System (AS),
uniquely identified by a number (AS number - ASN)
ASes can communicate to each other thanks to BGP, that
allow them to build routes toward Internet networks
A route is: “a unit of information that pairs a set of
destinations with the attributes of a path to those
destinations”
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
4 / 18
Data Gathering
Routes are stored in the RIB of each BGP router
It is possible to study the Internet at the AS-level of
abstraction exploting the AS path attribute
AS paths are gathered by route-collectors deployed by
RouteViews and RIPE-RIS projects
21,144,713 AS paths available (in October 2010)
36,437 ASes
116,671 connections
Usually the Internet is studied as an undirect graph, but this
not take into account the different economic relationships
existent among ASes
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
5 / 18
Economic Relationships
Typical economic relationships are:
provider-customer: the customer pays the provider to reach
all ASes that it cannot reach in other ways
peer-to-peer: the two ASes exploits each other to reach their
customer-cones (typically free-of-charge)
sibling-to-sibling: each AS acts as a provider for the other
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
6 / 18
Valley-free properties
Gao, in [1] pointed out that an AS should not transit traffic
between
X two of its peers
X two of its providers
X a peer and a provider
This leads to the valley-free property of AS paths:
A provider-customer edge can be followed by only
provider-customer or sibling-to-sibling edges
A peer-to-peer edge can be followed by only provider-customer
or sibling-to-sibling edges
[1] Gao L., On inferring autonomous system relationships in the internet, IEEE/ACM
Transactions on Networking, December 2001.
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
7 / 18
Tier-1 ASes
A Tier-1 AS is an AS that is able to reach all other Internet
AS without recurring to any provider, i.e. a Tier-1 AS has no
provider
In [2], Oliveira et al. exploited valley-free property of AS paths
and a list of Tier-1 ASes to build a new algorithm to infer AS
relationships
A non-Tier-1 AS should be able to reach all the Internet
networks, thus there must exist at least one AS path including
the considered AS and a Tier-1 AS
The valley-free property and the presence of Tier-1 into an AS
path, allow to infer the economic relationships between the
ASes forming the path
[2] Oliveira et al., The (in)Completeness of the Observed Internet AS-level Structure,
in IEEE/ACM Transactions on Networking, 2010.
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
8 / 18
Outline
1
Introduction and basilar concepts from previous works
2
Time-based tagging algorithm
3
Tagged topology analysis
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
9 / 18
Analysis of BGP data dynamics: methodology
Since ASes can change their decisions on how to reach ASes,
AS paths can change during time
The TIME information in update messages can be exploited to
trace the dynamics of AS paths
We consider as the lifespan of an AS path the max time span
in which it was considered as active by the BGP
i.e. the longest time interval during which there is at least one
active route that includes the considered AS path in its
attributes.
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
10 / 18
CCDF Lifespan of gathered AS paths
1
0.9
0.8
P(X > x)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0 0
10
10
1
10
2
10
3
10
4
10
5
10
6
10
7
Lifespan [s]
The CCDF highlights the presence of many short-lasting AS
paths:
AS paths that appear after the activation of a backup
connection
Transient AS paths caused by BGP misconfigurations that
appear only during the BGP convergence process after a
network failure
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
11 / 18
Tagging algorithm
step A: Inference of all the possible economic relationships for
each direct AS connection
direct means that (A,B) 6= (B,A)
It is based on the approach proposed by Oliveira et al. in [2]
The list of Tier-1 provided by Wikipedia has been exploited
For each tag is mantained the lifespan of the AS path used
At the end of this step we have multiple (tag, lifespan) pairs
for each connection
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
12 / 18
Tagging algorithm
step B: Inference of a single economic relationship for each
direct AS connection
All (tag, lifespan) pairs related to the same direct connection
have to be merged
Find the max lifespan among each pair
Merge only those pairs that have a comparable lifespan with
the max, i.e. those do not differ more than N order of
magnitude from the max
Record the largest lifespan as the lifespan of the resulting tag
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
[A, B]
p2c
[A, B]
p2p
c2p
s2s
p2c
p2p
c2p
s2s
p2c
p2c
s2s
s2s
p2c
p2p
c2p
s2s
s2s
c2p
c2p
s2s
s2s
s2s
s2s
s2s
BGP and inter-AS economic relationships
13 / 18
Tagging algorithm
step C: Final tagging and two-way validation
In order to have the economic relationship existing between AS
A and AS B, the tags inferred for (A,B) and (B,A) connections
have to be merged
The approach used is the same as Step B, considering the
different direction of connections, e.g. (A,B) = p2c and (B,A)
= c2p have the same meaning
The merge is still based on lifespan, thus if the lifespans are
not comparable, only the long-lasting tag affect the final tag
If there is a tag for both (A,B) and (B,A) and their lifespan is
comparable, then the tag is said to be two-way validated
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
14 / 18
Outline
1
Introduction Basilar concepts from previous works
2
Time-based tagging algorithm
3
Tagged topology analysis
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
15 / 18
Results
1
Results shows that if all the AS
paths were used, the probability
that transient AS paths affect
the final results is larger
MIN lifespan of accepted (tag, lifespan) pairs in Step B
0.9
0.8
P(X > x)
0.7
0.6
The set of reliable tags is
composed by the two-way
validate tags, that represents
only the 4.5-6.4%
0.5
0.4
0.3
0.2
0.1
N=1
N=2
N=INF.
0 0
10
1
10
2
10
3
10
4
10
5
10
6
10
NMAG
1
2
∞
Tag type
p2c
p2p
s2s
p2c
p2p
s2s
p2c
p2p
s2s
Total
71841
43398
1378
72394
42556
1667
74949
39078
2590
7
10
Lifespan [s]
The precision of the algorithm
suffers of the lack of information
One-way validated (%)
69707 (97.0%)
41507 (95.6%)
70034 (96.7%)
40716 (95.7%)
71642 (95.9%)
37235 (95.3%)
-
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
16 / 18
Stub ASes
NMAG
1
2
∞
Tag type
p2c
p2p
s2s
p2c
p2p
s2s
p2c
p2p
s2s
Total
71841
43398
1378
72394
42556
1667
74949
39078
2590
Involving Stubs (%)
53089 (73.8%)
12990 (29.9%)
53331 (73.7%)
12748 (30.0%)
54180 (72.3%)
11898 (30.5%)
-
The majority of the one-way validated connections are
involving to stub ASes
A stub AS is an AS that does not transit traffic for any other
AS
Since their nature, stub ASes are likely to be customers of
their neighbors
Considering this, the percentage of reliable tags rise to almost
56%
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
17 / 18
The End
Questions?
E. Gregori, A. Improta, L. Lenzini, L. Rossi, L. Sani
BGP and inter-AS economic relationships
18 / 18