Scale-invariant geometric random graphs

被引：5

作者：

Xie, Zheng ^{[1
]}

Rogers, Tim ^{[2
]}

机构：

[1] Natl Univ Def Technol, Coll Sci, Changsha 410073, Hunan, Peoples R China

[2] Univ Bath, Dept Math Sci, Ctr Networks & Collect Behav, Bath BA2 7AY, Avon, England

来源：

PHYSICAL REVIEW E | 2016年 / 93卷 / 03期

关键词：

NETWORKS;

D O I：

10.1103/PhysRevE.93.032310

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

We introduce and analyze a class of growing geometric random graphs that are invariant under rescaling of space and time. Directed connections between nodes are drawn according to influence zones that depend on node position in space and time, mimicking the heterogeneity and increased specialization found in growing networks. Through calculations and numerical simulations we explore the consequences of scale invariance for geometric random graphs generated this way. Our analysis reveals a dichotomy between scale-free and Poisson distributions of in-and out-degree, the existence of a random number of hub nodes, high clustering, and unusual percolation behavior. These properties are similar to those of empirically observed web graphs.

引用

页数：6

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