Connectivity and giant component in random distance graphs

preprint2015arXivOpen access

Abstract

Various different random graph models have been proposed in which the vertices of the graph are seen as members of a metric space, and edges between vertices are determined as a function of the distance between the corresponding metric space elements. We here propose a model G=G(X,f)G=G(X, f), in which (X,d)(X, d) is a metric space, V(G)=XV(G)=X, and P(u∼v)=f(d(u,v))\mathbb{P}(u\sim v) = f(d(u, v)), where ff is a decreasing function on the set of possible distances in XX. We consider the case that XX is the n×n×⋯×nn\times n \times \dots\times n integer lattice in dimension rr, with dd the ℓ1\ell_1 metric, and f(d)=1nβdf(d) = \frac{1}{n^βd}, and determine a threshold for the emergence of the giant component and connectivity in this model. We compare this model with a traditional Waxman graph. Further, we discuss expected degrees of nodes in detail for dimension 2.

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