English

Connectivity and giant component in random distance graphs

Combinatorics 2015-09-14 v1 Probability

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(uv)=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 1\ell_1 metric, and f(d)=1nβdf(d) = \frac{1}{n^\beta d}, 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.

Keywords

Cite

@article{arxiv.1509.03568,
  title  = {Connectivity and giant component in random distance graphs},
  author = {Joshua Flynn and Briana Oshiro and Mary Radcliffe},
  journal= {arXiv preprint arXiv:1509.03568},
  year   = {2015}
}
R2 v1 2026-06-22T10:54:44.241Z