Border trees of complex networks

TL;DR

This paper introduces a method to identify and analyze border trees in complex networks, revealing structural properties of network edges that are often overlooked, with applications to both theoretical models and real-world networks.

Contribution

It presents an algorithm for detecting border trees and explores their properties across various network types, enhancing understanding of network borders.

Findings

Border trees vary significantly across network models and real networks.

The number and structure of border trees correlate with network topology.

Border trees provide insights into network fragility and evolution.

Abstract

The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small world property of real networks were fundamental to stimulate more realistic models and to understand some dynamical processes such as network growth. However, properties related to the network borders (nodes with degree equal to one), one of its most fragile parts, remain little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze complex networks by looking for border trees, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider a series of their measurements, including their number of vertices, number of leaves, and depth. We investigate the properties of border trees for several theoretical models as well as real-world networks.