Using Spectral Radius Ratio for Node Degree to Analyze the Evolution of Scale Free Networks and Small World Networks

TL;DR

This paper introduces a spectral radius ratio based method to analyze and tune the evolution of scale-free and small-world networks, revealing strong correlations with node degree variation and aiding parameter optimization.

Contribution

It proposes using the spectral radius ratio for node degree as a new analytical tool for network evolution and parameter tuning.

Findings

High correlation between spectral radius ratio and node degree variation

Effective tuning of network evolution parameters using spectral radius ratio

Evaluation of link addition and rewiring impacts on network structure

Abstract

In this paper, we show the evaluation of the spectral radius for node degree as the basis to analyze the variation in the node degrees during the evolution of scale-free networks and small-world networks. Spectral radius is the principal eigenvalue of the adjacency matrix of a network graph and spectral radius ratio for node degree is the ratio of the spectral radius and the average node degree. We observe a very high positive correlation between the spectral radius ratio for node degree and the coefficient of variation of node degree (ratio of the standard deviation of node degree and average node degree). We show how the spectral radius ratio for node degree can be used as the basis to tune the operating parameters of the evolution models for scale-free networks and small-world networks as well as evaluate the impact of the number of links added per node introduced during the evolution of a scale-free network and evaluate the impact of the probability of rewiring during the evolution of a small-world network from a regular network.