On the Strength of Connectivity of Inhomogeneous Random K-out Graphs
Abstract
Random graphs are an important tool for modelling and analyzing the underlying properties of complex real-world networks. In this paper, we study a class of random graphs known as the inhomogeneous random K-out graphs which were recently introduced to analyze heterogeneous sensor networks secured by the pairwise scheme. In this model, first, each of the n nodes is classified as type-1 (respectively, type-2) with probability 0<μ<1 (respectively, 1-μ) independently from each other. Next, each type-1 (respectively, type-2) node draws 1 arc towards a node (respectively, Kn arcs towards Kn distinct nodes) selected uniformly at random, and then the orientation of the arcs is ignored. From the literature on homogeneous K-out graphs wherein all nodes select Kn neighbors (i.e., μ=0), it is known that when Kn ≥2, the graph is Kn-connected asymptotically almost surely (a.a.s.) as n gets large. In the inhomogeneous case (i.e., μ>0), it was recently established that achieving even 1-connectivity a.a.s. requires Kn=ω(1). Here, we provide a comprehensive set of results to complement these existing results. First, we establish a sharp zero-one law for k-connectivity, showing that for the network to be k-connected a.a.s., we need to set Kn = 11-μ( n +(k-2) n + ω(1)) for all k=2, 3, …. Despite such large scaling of Kn being required for k-connectivity, we show that the trivial condition of Kn ≥ 2 for all n is sufficient to ensure that inhomogeneous K-out graph has a connected component of size n-O(1) whp.
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