The Large Scale Curvature of Networks

TL;DR

This paper uncovers a global curvature property in large-scale networks that significantly influences core congestion, with load scaling as N^2, unlike flatter networks, based on analysis of real-world data.

Contribution

It introduces the concept of global curvature in networks and demonstrates its impact on congestion scaling through empirical analysis.

Findings

Core load scales as N^2 in curved networks

Flat networks have core load scaling as N^1.5

Global curvature affects network performance and congestion

Abstract

Understanding key structural properties of large scale networks are crucial for analyzing and optimizing their performance, and improving their reliability and security. Here we show that these networks possess a previously unnoticed feature, global curvature, which we argue has a major impact on core congestion: the load at the core of a network with N nodes scales as N^2 as compared to N^1.5 for a flat network. We substantiate this claim through analysis of a collection of real data networks across the globe as measured and documented by previous researchers.