1. Lecture 26:
Internet Topology
CS 765: Complex Networks

2. Web of interconnected networks
Internet
Web of interconnected networks
Grows with no central authority
Autonomous Systems optimize local communication efficiency
The building blocks are engineered and studied in depth
Global entity has not been characterized
Most real world complex-networks have non-trivial properties.
Global properties can not be inferred from local ones
Engineered with large technical diversity
Range from local campuses to transcontinental backbone providers

3. Internet Measurements
Need for Internet measurements arises due to commercial, social, and technical issues
Realistic simulation environment for developed products,
Improve network management
Robustness with respect to failures/attacks
Comprehend spreading of worms/viruses
Know social trends in Internet use
Scientific discovery
Scale-free (power-law), Small-world, Rich-club, Dissasortativity,…
Topology collection is hard as ISPs do not share their internal topology info by default
Complex networks are being analyzed for their growth mechanism and topological characteristics.
Scale-free (Power-law)
Small-world (6 degree of separation)
Dissasortative mixing (degree-degree correlation)
Rich-club phenomenon (tightly interconnected core)

4. Internet Topology Measurement
CAIDA 2006

5. Internet Topology Measurement
CAIDA 2006 5

6. Internet Topology Measurement

7. Internet Topology Measurement
CAIDA 2006 7

8. Internet Topology Measurements Probing
Direct probing
Indirect probing
IPB
IPD
Vantage Point
IPB TTL=64
IPD TTL=64 B C D A A D B C
Vantage Point
IPB
IPC
IPD TTL=1
IPD TTL=2 8

9. Internet Topology Measurement Topology Collection (traceroute)
Probe packets are carefully constructed to elicit intended response from a probe destination
traceroute probes all nodes on a path towards a given destination
TTL-scoped probes obtain ICMP error messages from routers on the path
ICMP messages includes the IP address of intermediate routers as its source
Merging end-to-end path traces yields the network map
IPA
IPB
IPC
IPD
Vantage Point
Destination
TTL=4
TTL=3
TTL=1
TTL=2 A B C D S 9

10. Internet Topology Measurement: Background
Internet2 backbone S
s.3
s.2
s.2
n.1 N
n.3
n.3
c.2
u.1
w.2
c.1
w.1 W C
c.3
u.2
w.3
w.3 U
k.1
c.4
k.2
u.3 K
l.1
k.3
a.1
Trace to NY L
l.2
a.2 A
(k,m)- traceroute
l.3
l.3
a.3
a.3
Trace to Seattle
h.2 H
h.1
h.3
h.4
h.4
h.4 d

11. Internet Topology Measurement: Backgroundf S
s.3
n.2
s.2
n.1 N
n.3
c.2
u.1
c.1
w.1
w.2 W C
c.3
u.2
w.3 U
k.1
c.4
k.2
u.3 K
l.1
k.3
a.1 L
l.2
a.2 A
(n,n)- traceroute
l.3
a.3
h.2 H
h.1
h.3
h.4 d

12. Topology Sampling Issues
Sampling to discover networks
Infer characteristics of the topology
Different studies considered
Effect of sample size [Barford 01]
Sampling bias [Lakhina 03]
Path accuracy [Augustin 06]
Sampling approach [Gunes 07]
Utilized protocol [Gunes 08]
ICMP echo request
TCP syn
UDP port unreachable

13. Anonymous Router Resolution Problem
Anonymous routers do not respond to traceroute probes and appear as a  in path traces
Same router may appear as a  in multiple traces.
Anonymous nodes belonging to the same router should be resolved.
Anonymity Types
Ignore all ICMP packets
ICMP rate-limiting
Ignore ICMP when congested
Filter ICMP at border

14. Anonymous Router Resolution Problem
Internet2 backbone f e S N C W U K L A H
Traces
d -  - L - S - e
d -  - A - W -  - f
e - S - L -  - d
e - S - U -  - C -  - f
f -  - C -  -  - d
f -  - C -  - U - S - e d

15. Anonymous Router Resolution ProblemK C N f L H A W e
Traces
d -  - L - S - e
d -  - A - W -  - f
e - S - L -  - d
e - S - U -  - C -  - f
f -  - C -  -  - d
f -  - C -  - U - S - e d
Sampled network d e f S U L C A W
Resulting network

16. Graph Based Induction Common Structuresx C y2 y1 y3  A x C y2 y1 y3 
Parallel nodes A C x y D w F v E z  A C x y D w E z  D A w x C y E z 
Clique
Complete Bipartite
Star
Parallel *-substrings is equivalent to Initial Pruning
Star is equivalent to neighbor matching A C x y D w F v E z  A C x y D w E z  D A w x C y E z 

17. Alias Resolution: .33 Each interface of a router has an IP address. .5
A router may respond with
different IP addresses to
different queries.
Alias Resolution is the process of grouping the interface IP addresses of each router into a single node.
Inaccuracies in alias resolution may result in a network map that
includes artificial links/nodes
misses existing links .5
.18
Denver .7
.13

18. IP Alias Resolution Problemf S
s.3
n.2
s.2
n.1 N
n.3
c.2
u.1
c.1
w.1
w.2 C W
u.2
c.3 U
k.1
w.3
c.4
k.2
u.3 K
k.3
l.1
l.2
a.1 L
a.2 A
l.3
a.3
h.2 H
Traces
d - h.4 - l.3 - s.2 - e
d - h.4 - a.3 - w.3 - n.3 - f
e - s.1 - l.1 - h.1 - d
e - s.1 - u.1 - k.1 - c.1 - n.1 - f
f - n.2 - c.2 - k.2 - h.2 - d
f - n.2 - c.2 - k.2 - u.2 - s.3 - e
h.3
h.1
h.4 d

19. IP Alias Resolution ProblemK C N
Sampled network f L H A W e d
Sample map without alias resolution
s.3
s.1
s.2
l.3
l.1
u.1
u.2
k.1
c.1
n.1
n.2
k.2
c.2
w.3
a.3
h.2
h.4
h.1 e d f
n.3
Traces
d - h.4 - l.3 - s.2 - e
d - h.4 - a.3 - w.3 - n.3 - f
e - s.1 - l.1 - h.1 - d
e - s.1 - u.1 - k.1 - c.1 - n.1 - f
f - n.2 - c.2 - k.2 - h.2 - d
f - n.2 - c.2 - k.2 - u.2 - s.3 - e 19

20. Genuine Subnet Resolution Problem
Alias resolution
IP addresses that belong to the same router
Subnet resolution
IP addresses that are connected over the same medium
IP2
IP3
IP4
IP1
IP6
IP5
IP1
IP1
IP2
IP3
IP2
IP3

21. Cheleby System Overview
PlanetLab
Vantage Points
Traces
x -  - L.2 - S.2 - y
x -  - A.1 - W.1 -  - z
y - S.1 - L.1 -  - x
y - S.1 – U.1 -  - C.1 -  - z
z -  - C.2 -  -  - x
z -  - C.2 -  - U.2 - S.3 - y
Initial Pruner (IP)
Structural Graph Indexer (SGI)
Raw Data
SubNet Inferrer (SNI) U K C N L H A W S x y z
Graph Based Induction (GBI)
Analytical IP Alias Resolver v (APARv2), iffinder
Network Topology
Cheleby: Subnet-Level Internet Topology

22. Exponents : -2.17, -2.02, -1.92, respectively
Degree Distribution
Exponents : -2.17, -2.02, -1.92, respectively
Avr: -2.04
Cheleby: Subnet-Level Internet Topology

23. Interface Distribution
Exponents : -2.71, -2.69, -2.74, respectively
Avr: -2.71
Cheleby: Subnet-Level Internet Topology

24. Exponents : -3.42, 3.62, respectively
Subnet Distribution
Exponents : -3.42, 3.62, respectively
Avr: -3.52
Nodes in Subnets
Cheleby: Subnet-Level Internet Topology

25. Synthetic Topology Generation
Network Size
ID
SD
Generate Nodes
Generate Subnets
Heterogeneous Swap
Calculate Degree Distribution based on DD
Satisfies Subnet & Interface Distributions !!! no
Match ?
Final Topology
yes
Cheleby: Subnet-Level Internet Topology

26. Connectivity Analysis
Relation between Interface Distribution and Number of Subnets
Single connected component is feasible only when
connectivity parameter <1
Feasible Region
Cheleby: Subnet-Level Internet Topology

27. Autonomous System Level