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The Geography and Evolution of the European Internet Infrastructure. Sandra Vinciguerra URU – Utrecht University European Fiber-Optic Networks.

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the geography and evolution of the european internet infrastructure

The Geography and Evolution of the European Internet Infrastructure

Sandra Vinciguerra

URU – Utrecht University

european fiber optic networks
European Fiber-Optic Networks

The research project is about the diffusion of internet fiber-optic backbone network all over Europe, on a network topological point of view.

Research question: how can we explain the geography, topology and different bandwidth of the current fiber-optic network?

research proposal
Research Proposal

The proposal is to find out statistically the reasons why some cities become hubs, more than others. We have to consider:

  • time of entry in the network;
  • their geographical location (near sea);
  • the physical distances between cities;
  • regional-economic variables such as Gross Regional Product;
  • the concentration of Internet-using firms;
  • demographic variables such as population density.

On the basis of the Barabàsi’s model, we would like to build a new model in order to explain how the network developed, then test this model with data on internet fiber-optic backbone network in Europe.

barab si s scale free networks
Barabàsi’s Scale Free Networks

SF networks are characterized by the presence of a less number of nodes highly connected – hubs – while the majority of nodes have only a few links.

SF modelis based on two mechanisms (Barabási and Albert, 1999):

  • Incremental Growth: networks are dynamic systems, the number of nodes grows with time;
  • Preferential Attachment: new vertices are not randomly connected to the existing nodes; they are linked with greater likelihood to high connectivity degree vertices.

(k is the degree of node i )

the new model
The New Model

On the basis of the Barabasi’s model we would like to build a new model adding the geographical distance between the nodes in the mechanism of preferential attachment (and try also to apply it, for instance, to the airport network).

Physical distances are impotant in terms of relative costs to cable.

New nodes prefer to connect to highly connected nodes to access to routers with a high bandwidth (lowering the cost of communication).

New connections may be well by-pass the nodes that are geographically closest and thus cheapest in terms of cable length. Emerging hubs are not expected to be located near one another.


Time series data are needed for all the variables taken in account, the period is relatively short (1989-2005)

Most of the varables are available at NUTS3 level – some are already available at URU or can simply be obtained through RPB or Eurostat

Special attention has to be paid on bandwidth price and capacity, which are not available both for a long period

Some data have to be integrated with data – they also provide data information on time of entry of a node and it’s location

internet infrastructure network
Internet Infrastructure Network

We expect a network not so densely connected while the cost of new connections are higher than the cost of introducing new nodes.

It’s an endogenous growth process: growth in bandwidth attracts high-end Internet activity, which in turn expands the local demand for higher bandwidth, which stimulates further growth in bandwidth, and so forth.

We expect to be able to explain a large part of the variance in bandwidth capacity and price. The specific local strategies of research institutions, business and governments are not captured by the statistical analysis.

ideal econometric model
Ideal Econometric Model

Dependent variable should indicate the importance of the node in the network like degree of a node (hubs) or another index like the betweness centrality (related to the paths) or bandwidth

Explanatory variables

  • classical demographic variables (population density, GDP, ..)
  • presence of a university in the region
  • concentration of Internet-using firms (banks, high-tech firms,…)
philosophical questions
Philosophical Questions

Time Series or Panel Data?

Wich kind of model?

OLS – GMM – Bayesian - ?????

I would like to draw the EVOLUTION in time and space of the network

I’m going to struggle with endogeneity and everything else…….

internet map

Thank you