Distributed Algorithm to Locate Critical Nodes to Network Robustness based on Spectral Analysis

TL;DR

This paper introduces a localized spectral analysis algorithm to identify critical nodes affecting network robustness, enabling navigation towards these nodes using only local information, with proven effectiveness across various network types.

Contribution

The paper presents a novel localized spectral analysis method for identifying critical nodes and a navigation procedure based solely on local information.

Findings

Effective identification of critical nodes across different network scales.

Successful navigation towards critical nodes using only local spectral data.

Validated robustness improvements in experimental networks.

Abstract

We propose an algorithm to locate the most critical nodes to network robustness. Such critical nodes may be thought of as those most related to the notion of network centrality. Our proposal relies only on a localized spectral analysis of a limited subnetwork centered at each node in the network. We also present a procedure allowing the navigation from any node towards a critical node following only local information computed by the proposed algorithm. Experimental results confirm the effectiveness of our proposal considering networks of different scales and topological characteristics.