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Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Modeling the evolution of the AS-level
Internet: Integrating aspects of traffic,
geography and economy
Petter Holme, Josh Karlin, Stephanie Forrest
Royal Institute of Technology, School of Computer Science and Technology
October 8, 2008
http://www.csc.kth.se/∼pholme/
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Autonomous Systems
Internet is divided into different
subnetworks—Autonomous Systems (AS)
An IP network (or collection of IP networks) with the same
routing policy.
Typically one AS corresponds to one administrative unit.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Autonomous Systems
Internet is divided into different
subnetworks—Autonomous Systems (AS)
An IP network (or collection of IP networks) with the same
routing policy.
Typically one AS corresponds to one administrative unit.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Autonomous Systems
Internet is divided into different
subnetworks—Autonomous Systems (AS)
An IP network (or collection of IP networks) with the same
routing policy.
Typically one AS corresponds to one administrative unit.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Autonomous Systems
Internet is divided into different
subnetworks—Autonomous Systems (AS)
An IP network (or collection of IP networks) with the same
routing policy.
Typically one AS corresponds to one administrative unit.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
BGP routing
Border Gateway Protocol determines how packets are
routed between ASes
Each server keeps a list of paths it can route a packets
through.
Policy (economical agreements) determines the order of
paths.
→ a hierarchy where packets are routed up (to provider),
sideways (to peer), and downwards (to customer).
A BGP server has a quite incomplete picture of the whole
AS-graph.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Degree distribution
Broad degree-distribution (possibly power-law, or log-normal).
1 10 100 1000
k
10−4
10−3
0.01
0.1
1
P(k)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Mechanistic models of AS graph
Typically focus on network topology.
. . . possibly with a geometry.
. . . or traffic.
No geographically explicit ASes.
No explicit economic modeling (pricing, etc.)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Barab´asi–Albert model
probability of attachment: ∝ ki
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Barab´asi–Albert model
probability of attachment: ∝ ki
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Barab´asi–Albert model
probability of attachment: ∝ ki
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Barab´asi–Albert model
probability of attachment: ∝ ki
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Barab´asi–Albert model
probability of attachment: ∝ ki
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
0
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
|r1 − r0|
0
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
FKP model
0
attach i to vertex j minimizing:
|ri − rj| + αd( j, 0)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial structure
Plot quantities as function of the average distance to the rest of
the AS graph.
P. Holme, J. Karlin and S. Forrest, Proc. R. Soc. A 463,
1231–1246 (2007).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial structure
0
0.05
0.1
0.15
0.2
2 3 4 5 6 7
average distance, ¯d
AS ’06
BA model
Inet model
fractionofvertices
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial structure
AS ’06
BA model
Inet model
1
10
100
1000
2 3 4 5 6 7
average distance, ¯d
averagedegree,k
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial structure
AS ’06
BA model
Inet model
0
0.05
0.1
0.15
0.2
clusteringcoefficient,C
2 3 4 5 6 7
average distance, ¯d
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial structure
AS ’06
BA model
Inet model
0.01deletionimpact,φ
2 3 4 5 6 7
average distance, ¯d
10−6
10−5
10−4
10−3
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
has spatially explicit ASes
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
has spatially explicit ASes
flowing between them
with realistic traffic
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
has spatially explicit ASes
flowing between them
with realistic traffic
that give the ASes income
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
has spatially explicit ASes
flowing between them
with realistic traffic
that give the ASes income
that the AS can invest in geographical growth
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Aim
Make a mechanistic model that:
has spatially explicit ASes
flowing between them
with realistic traffic
that increase / affect
the traffic
that give the ASes income
that the AS can invest in geographical growth
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Overall structure
The model begins with one agent located at the pixel with the
highest population density. The model then iterates over the
following steps:
1 Network growth. The number of agents is increased. The
agents are expanded geometrically, and their capacities
are adjusted.
2 Network traffic. Messages are created, migrated toward
their targets, and delivered. This process is repeated
Ntraffic times before the next network-growth step.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Overall structure
The model begins with one agent located at the pixel with the
highest population density. The model then iterates over the
following steps:
1 Network growth. The number of agents is increased. The
agents are expanded geometrically, and their capacities
are adjusted.
2 Network traffic. Messages are created, migrated toward
their targets, and delivered. This process is repeated
Ntraffic times before the next network-growth step.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Overall structure
The model begins with one agent located at the pixel with the
highest population density. The model then iterates over the
following steps:
1 Network growth. The number of agents is increased. The
agents are expanded geometrically, and their capacities
are adjusted.
2 Network traffic. Messages are created, migrated toward
their targets, and delivered. This process is repeated
Ntraffic times before the next network-growth step.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
set of links (to AS at same pixel)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
budget
set of links (to AS at same pixel)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
budget
set of links (to AS at same pixel)
queue
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
budget
capacity
set of links (to AS at same pixel)
queue
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
budget
capacity
set of links (to AS at same pixel)
queue
costs for: increasing capacity
connecting to other, adding loc.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
geography represented as sq. grid
each pixel has a pop. density
the ASes are modeled as:
a set of locations (coordinates)
budget
capacity
set of links (to AS at same pixel)
queue
costs for: increasing capacity
connecting to other, adding loc.
income prop. to traffic
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
connect unconnected pairs at random
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
connect unconnected pairs at random
(if both ASes can afford a connection)
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
connect unconnected pairs at random
(if both ASes can afford a connection)
4. spatial extension
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
connect unconnected pairs at random
(if both ASes can afford a connection)
4. spatial extension
ASes spend their budget on new loc
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Network Growth
1. (while nwk too dense,) add ASes
2. increase capacity as much as needed
3. link addition
connect unconnected pairs at random
(if both ASes can afford a connection)
4. spatial extension
ASes spend their budget on new loc
choose affordable pixel w highest pop
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
s
t
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
s
t s
t
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
t = 1
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
t = 2
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic dynamics
t = 3
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Time evolution
a
b
c
τp,d
100
104
1
103
number of agents, n
number of links, m
n,mfractionoftotal
0.25
0.5
0.75
0
covered population
covered area
120 140 160 200180
120 140 160 200
time, τ
2
3
4
5
6
7
d
τp
100180 100001000
time, τ number of ASs, n
8
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Degree distribution
1 10 100 1000 1 10 100 1000 1 100 100010
k k k
10−4
10−3
0.01
0.1
1
P(k)
real
model 10−4
10−3
0.01
0.1
1
BA model
P(k)
10−3
0.01
0.1
1
P(k)
FKP model
10−4
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Degree distribution
10−5
10−6
10−4
10−3
1
10
104
104
105
106
103
traffic load
degree,k
100
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial statistics
0
0.1
0.2
our model
AS06 FKPBA
fractionofvertices
5 6 5 65 6 3 4 3 43 4
average distance, ¯d average distance, ¯d average distance, ¯d
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Radial statistics
3 4 3 43 4
average distance, ¯d average distance, ¯d average distance, ¯d
5 6 5 65 6
averagedegree
1
10
102
103
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Traffic vs centrality
10−6
10−3
10−4
10−5
10−1
10−2
10−4
10−3
10−5
1 5 10 50
trafficdensity,ρ
betweenness, CB ×104
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
100 200 300
population density (people per square mile)
0
t = 14
λ = 6
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
100 200 300
population density (people per square mile)
0
λ = 15
t = 23
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
100 200 300
population density (people per square mile)
0
t = 28
λ = 69
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
100 200 300
population density (people per square mile)
0
λ = 272
t = 28
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Geography
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Summary
Mechanistic growth model of AS-level Internet
Degree distribution matches
Periphery not as complex as reality
Traffic fluctuations affect low- and medium-sized ASes
Spatial distribution not completely crazy
P. Holme, J. Karlin and S. Forrest, An integrated model of
traffic, geography and economy in the Internet. Computer
Communication Review 32, 7–15 (2008).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Other integrative mechanistic models
S. Shakkottai et al.. Evolution of the Internet Ecosystem.
S. Bar, M. Gonen & A. Wool. A geographic directed
preferential Internet topology model. Computer Networks
51, 4174–4188 (2007).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Other integrative mechanistic models
S. Shakkottai et al.. Evolution of the Internet Ecosystem.
S. Bar, M. Gonen & A. Wool. A geographic directed
preferential Internet topology model. Computer Networks
51, 4174–4188 (2007).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Other integrative mechanistic models
S. Shakkottai et al.. Evolution of the Internet Ecosystem.
S. Bar, M. Gonen & A. Wool. A geographic directed
preferential Internet topology model. Computer Networks
51, 4174–4188 (2007).
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Future
Including economy.
Simple models.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Future
Including economy.
Simple models.
Modeling the
evolution of
the AS-level
Internet:
Integrating
aspects of
traffic,
geography
and economy
PETTER
HOLME
Introduction
Our model
Numerical
results
Future
Including economy.
Simple models.

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Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy

  • 1. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy Petter Holme, Josh Karlin, Stephanie Forrest Royal Institute of Technology, School of Computer Science and Technology October 8, 2008 http://www.csc.kth.se/∼pholme/
  • 2. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Autonomous Systems Internet is divided into different subnetworks—Autonomous Systems (AS) An IP network (or collection of IP networks) with the same routing policy. Typically one AS corresponds to one administrative unit.
  • 3. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Autonomous Systems Internet is divided into different subnetworks—Autonomous Systems (AS) An IP network (or collection of IP networks) with the same routing policy. Typically one AS corresponds to one administrative unit.
  • 4. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Autonomous Systems Internet is divided into different subnetworks—Autonomous Systems (AS) An IP network (or collection of IP networks) with the same routing policy. Typically one AS corresponds to one administrative unit.
  • 5. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Autonomous Systems Internet is divided into different subnetworks—Autonomous Systems (AS) An IP network (or collection of IP networks) with the same routing policy. Typically one AS corresponds to one administrative unit.
  • 6. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 7. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 8. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 9. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 10. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 11. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results BGP routing Border Gateway Protocol determines how packets are routed between ASes Each server keeps a list of paths it can route a packets through. Policy (economical agreements) determines the order of paths. → a hierarchy where packets are routed up (to provider), sideways (to peer), and downwards (to customer). A BGP server has a quite incomplete picture of the whole AS-graph.
  • 12. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Degree distribution Broad degree-distribution (possibly power-law, or log-normal). 1 10 100 1000 k 10−4 10−3 0.01 0.1 1 P(k)
  • 13. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 14. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 15. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 16. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 17. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 18. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Mechanistic models of AS graph Typically focus on network topology. . . . possibly with a geometry. . . . or traffic. No geographically explicit ASes. No explicit economic modeling (pricing, etc.)
  • 19. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Barab´asi–Albert model probability of attachment: ∝ ki
  • 20. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Barab´asi–Albert model probability of attachment: ∝ ki
  • 21. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Barab´asi–Albert model probability of attachment: ∝ ki
  • 22. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Barab´asi–Albert model probability of attachment: ∝ ki
  • 23. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Barab´asi–Albert model probability of attachment: ∝ ki
  • 24. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model attach i to vertex j minimizing: |ri − rj| + αd( j, 0) 0
  • 25. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model attach i to vertex j minimizing: |ri − rj| + αd( j, 0) |r1 − r0| 0
  • 26. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 27. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 28. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 29. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 30. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 31. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results FKP model 0 attach i to vertex j minimizing: |ri − rj| + αd( j, 0)
  • 32. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial structure Plot quantities as function of the average distance to the rest of the AS graph. P. Holme, J. Karlin and S. Forrest, Proc. R. Soc. A 463, 1231–1246 (2007).
  • 33. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial structure 0 0.05 0.1 0.15 0.2 2 3 4 5 6 7 average distance, ¯d AS ’06 BA model Inet model fractionofvertices
  • 34. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial structure AS ’06 BA model Inet model 1 10 100 1000 2 3 4 5 6 7 average distance, ¯d averagedegree,k
  • 35. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial structure AS ’06 BA model Inet model 0 0.05 0.1 0.15 0.2 clusteringcoefficient,C 2 3 4 5 6 7 average distance, ¯d
  • 36. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial structure AS ’06 BA model Inet model 0.01deletionimpact,φ 2 3 4 5 6 7 average distance, ¯d 10−6 10−5 10−4 10−3
  • 37. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that:
  • 38. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that: has spatially explicit ASes
  • 39. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that: has spatially explicit ASes flowing between them with realistic traffic
  • 40. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that: has spatially explicit ASes flowing between them with realistic traffic that give the ASes income
  • 41. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that: has spatially explicit ASes flowing between them with realistic traffic that give the ASes income that the AS can invest in geographical growth
  • 42. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Aim Make a mechanistic model that: has spatially explicit ASes flowing between them with realistic traffic that increase / affect the traffic that give the ASes income that the AS can invest in geographical growth
  • 43. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Overall structure The model begins with one agent located at the pixel with the highest population density. The model then iterates over the following steps: 1 Network growth. The number of agents is increased. The agents are expanded geometrically, and their capacities are adjusted. 2 Network traffic. Messages are created, migrated toward their targets, and delivered. This process is repeated Ntraffic times before the next network-growth step.
  • 44. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Overall structure The model begins with one agent located at the pixel with the highest population density. The model then iterates over the following steps: 1 Network growth. The number of agents is increased. The agents are expanded geometrically, and their capacities are adjusted. 2 Network traffic. Messages are created, migrated toward their targets, and delivered. This process is repeated Ntraffic times before the next network-growth step.
  • 45. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Overall structure The model begins with one agent located at the pixel with the highest population density. The model then iterates over the following steps: 1 Network growth. The number of agents is increased. The agents are expanded geometrically, and their capacities are adjusted. 2 Network traffic. Messages are created, migrated toward their targets, and delivered. This process is repeated Ntraffic times before the next network-growth step.
  • 46. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid
  • 47. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density
  • 48. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as:
  • 49. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates)
  • 50. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) set of links (to AS at same pixel)
  • 51. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) budget set of links (to AS at same pixel)
  • 52. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) budget set of links (to AS at same pixel) queue
  • 53. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) budget capacity set of links (to AS at same pixel) queue
  • 54. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) budget capacity set of links (to AS at same pixel) queue costs for: increasing capacity connecting to other, adding loc.
  • 55. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth geography represented as sq. grid each pixel has a pop. density the ASes are modeled as: a set of locations (coordinates) budget capacity set of links (to AS at same pixel) queue costs for: increasing capacity connecting to other, adding loc. income prop. to traffic
  • 56. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth
  • 57. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes
  • 58. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed
  • 59. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition
  • 60. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition connect unconnected pairs at random
  • 61. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition connect unconnected pairs at random (if both ASes can afford a connection)
  • 62. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition connect unconnected pairs at random (if both ASes can afford a connection) 4. spatial extension
  • 63. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition connect unconnected pairs at random (if both ASes can afford a connection) 4. spatial extension ASes spend their budget on new loc
  • 64. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Network Growth 1. (while nwk too dense,) add ASes 2. increase capacity as much as needed 3. link addition connect unconnected pairs at random (if both ASes can afford a connection) 4. spatial extension ASes spend their budget on new loc choose affordable pixel w highest pop
  • 65. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics
  • 66. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics
  • 67. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics
  • 68. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics s t
  • 69. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics s t s t
  • 70. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics t = 1
  • 71. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics t = 2
  • 72. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic dynamics t = 3
  • 73. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Time evolution a b c τp,d 100 104 1 103 number of agents, n number of links, m n,mfractionoftotal 0.25 0.5 0.75 0 covered population covered area 120 140 160 200180 120 140 160 200 time, τ 2 3 4 5 6 7 d τp 100180 100001000 time, τ number of ASs, n 8
  • 74. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Degree distribution 1 10 100 1000 1 10 100 1000 1 100 100010 k k k 10−4 10−3 0.01 0.1 1 P(k) real model 10−4 10−3 0.01 0.1 1 BA model P(k) 10−3 0.01 0.1 1 P(k) FKP model 10−4
  • 75. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Degree distribution 10−5 10−6 10−4 10−3 1 10 104 104 105 106 103 traffic load degree,k 100
  • 76. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial statistics 0 0.1 0.2 our model AS06 FKPBA fractionofvertices 5 6 5 65 6 3 4 3 43 4 average distance, ¯d average distance, ¯d average distance, ¯d
  • 77. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Radial statistics 3 4 3 43 4 average distance, ¯d average distance, ¯d average distance, ¯d 5 6 5 65 6 averagedegree 1 10 102 103
  • 78. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Traffic vs centrality 10−6 10−3 10−4 10−5 10−1 10−2 10−4 10−3 10−5 1 5 10 50 trafficdensity,ρ betweenness, CB ×104
  • 79. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography 100 200 300 population density (people per square mile) 0 t = 14 λ = 6
  • 80. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography 100 200 300 population density (people per square mile) 0 λ = 15 t = 23
  • 81. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography 100 200 300 population density (people per square mile) 0 t = 28 λ = 69
  • 82. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography 100 200 300 population density (people per square mile) 0 λ = 272 t = 28
  • 83. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography
  • 84. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Geography
  • 85. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 86. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 87. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 88. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 89. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 90. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 91. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Summary Mechanistic growth model of AS-level Internet Degree distribution matches Periphery not as complex as reality Traffic fluctuations affect low- and medium-sized ASes Spatial distribution not completely crazy P. Holme, J. Karlin and S. Forrest, An integrated model of traffic, geography and economy in the Internet. Computer Communication Review 32, 7–15 (2008).
  • 92. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Other integrative mechanistic models S. Shakkottai et al.. Evolution of the Internet Ecosystem. S. Bar, M. Gonen & A. Wool. A geographic directed preferential Internet topology model. Computer Networks 51, 4174–4188 (2007).
  • 93. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Other integrative mechanistic models S. Shakkottai et al.. Evolution of the Internet Ecosystem. S. Bar, M. Gonen & A. Wool. A geographic directed preferential Internet topology model. Computer Networks 51, 4174–4188 (2007).
  • 94. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Other integrative mechanistic models S. Shakkottai et al.. Evolution of the Internet Ecosystem. S. Bar, M. Gonen & A. Wool. A geographic directed preferential Internet topology model. Computer Networks 51, 4174–4188 (2007).
  • 95. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Future Including economy. Simple models.
  • 96. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Future Including economy. Simple models.
  • 97. Modeling the evolution of the AS-level Internet: Integrating aspects of traffic, geography and economy PETTER HOLME Introduction Our model Numerical results Future Including economy. Simple models.