Preferential Behaviour and Scaling in Diffusive Dynamics on Networks

TL;DR

This paper investigates how preferential behaviors influence fluctuation scaling in diffusive processes on inhomogeneous scale-free networks, revealing that preferences lead to non-universal scaling exponents and cooperative dynamics.

Contribution

It demonstrates the role of preferential behavior in inducing non-universal fluctuation scaling in network diffusion, contrasting with non-preferential dynamics.

Findings

Scaling in fluctuations depends on preferential behavior.

Scaling exponents vary with time window and preference.

Cooperative behavior underpins the observed scaling patterns.

Abstract

We study the fluctuation properties and return-time statistics on inhomogeneous scale-free networks using packets moving with two different dynamical rules; random diffusion and locally navigated diffusive motion with preferred edges. Scaling in the fluctuations occurs when the dispersion of a quantity at each node or edge increases like the its mean to the power $\mu$. We show that the occurrence of scaling in the fluctuations of both the number of packets passing nodes and the number flowing along edges is related to preferential behaviour in either the topology (in the case of nodes) or in the dynamics (in case the of edges). Within our model the absence of any preference leads to the absence of scaling, and when scaling occurs it is non-universal; for random diffusion the number of packets passing a node scales with an exponent $\mu$ which increases continuously with increased acquisition time window from $\mu =1/2$ at small windows, to $\mu =1$ at long time windows; In the preferentially navigated diffusive motion, busy nodes and edges have exponent $\mu =1$, in contrast to less busy parts of the network, where an exponent $\mu =1/2$ is found. Broad distributions of the return times at nodes and edges illustrate that the basis of the observed scaling is the cooperative behaviour between groups of nodes or edges. These conclusions are relevant for a large class of diffusive dynamics on networks, including packet transport with local navigation rules.