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Pré-Publication, Document De Travail Année : 2015

ROBUSTNESS OF SCALE-FREE SPATIAL NETWORKS

Résumé

A growing family of random graphs is called robust if it retains a giant component after percolation with arbitrary positive retention probability. We study robustness for graphs, in which new vertices are given a spatial position on the d-dimensional torus and are connected to existing vertices with a probability favouring short spatial distances and high degrees. In this model of a scale-free network with clustering we can independently tune the power law exponent τ of the degree distribution and the rate −δd at which the connection probability decreases with the distance of two vertices. We show that the network is robust if τ < 2 + 1 δ , but fails to be robust if τ > 3. In the case of one-dimensional space we also show that the network is not robust if τ > 2 + 1 δ−1. This implies that robustness of a scale-free network depends not only on its power-law exponent but also on its clustering features. Other than the classical models of scale-free networks our model is not locally tree-like, and hence we need to develop novel methods for its study, including, for example, a surprising application of the BK-inequality.
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Dates et versions

hal-01139102 , version 1 (03-04-2015)

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Emmanuel Jacob, Morters Peter. ROBUSTNESS OF SCALE-FREE SPATIAL NETWORKS. 2015. ⟨hal-01139102⟩
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