Realistic searches on stretched exponential networks

TL;DR

This paper studies search schemes on networks with stretched exponential degree distributions, analyzing how social distance-dependent linking probabilities affect search success and the emergence of small-world effects.

Contribution

It introduces a realistic search model on stretched exponential networks considering social distance effects and characterizes conditions for small-world behavior.

Findings

Success rate scales as N^(-delta) with network size

Dynamic small world effect exists in a specific parameter region

Search efficiency depends on social distance and degree distribution parameters

Abstract

We consider navigation or search schemes on networks which have a degree distribution of the form $P(k) \propto \exp(-k^\gamma)$. In addition, the linking probability is taken to be dependent on social distances and is governed by a parameter $\lambda$. The searches are realistic in the sense that not all search chains can be completed. An estimate of $\mu=\rho/s_d$, where $\rho$ is the success rate and $s_d$ the dynamic path length, shows that for a network of $N$ nodes, $\mu \propto N^{-\delta}$ in general. Dynamic small world effect, i.e., $\delta \simeq 0$ is shown to exist in a restricted region of the $\lambda-\gamma$ plane.