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Characterizing several properties of high-dimensional random Apollonian networks

2019/01/21 by Zhang, Panpan
#FOS: Mathematics #Probability (math.PR)

paper · doi:10.48550/arxiv.1901.07073

Abstract

In this article, we investigate several properties of high-dimensional random Apollonian networks (HDRANs), including two types of degree profiles, the small-world effect (clustering property), sparsity, and three distance-based metrics. The characterizations of degree profiles are based on several rigorous mathematical and probabilistic methods, such as a two-dimensional mathematical induction, analytic combinatorics, and Pólya urns, etc. The small-world property is uncovered by a well-developed measure---local clustering coefficient, and the sparsity is assessed by a proposed Gini index. Finally, we look into three distance-based properties; they are total depth, diameter and Wiener index.

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