Scaling breakdown in flow fluctuations on complex networks

TL;DR

This paper investigates flow fluctuations in complex networks using a random diffusion model, revealing that power-law scaling of fluctuations does not universally hold due to the interplay of dynamical, topological, and statistical factors.

Contribution

It introduces an analytical law describing how flow fluctuations depend on mean traffic, demonstrating the breakdown of universal power-law scaling in various network scenarios.

Findings

Flow fluctuations are governed by dynamical, topological, and statistical factors.

Universal power-law scaling of flow fluctuations does not always occur.

The scaling breakdown is validated through traffic algorithms and real data analysis.

Abstract

We propose a model of random diffusion to investigate flow fluctuations in complex networks. We derive an analytical law showing that the dependence of fluctuations with the mean traffic in a network is ruled by the delicate interplay of three factors, respectively of dynamical, topological and statistical nature. In particular, we demonstrate that the existence of a power-law scaling characterizing the flow fluctuations at every node in the network can not be claimed for. We show the validity of this scaling breakdown under quite general topological and dynamical situations by means of different traffic algorithms and by analyzing real data.