University of Leicester
Browse
s41598-017-12589-9.pdf (2.45 MB)

Self-organisation of small-world networks by adaptive rewiring in response to graph diffusion

Download (2.45 MB)
journal contribution
posted on 2018-02-19, 16:38 authored by Nicholas Jarman, Erik Steur, Chris Trengove, Ivan Y. Tyukin, Cees Van Leeuwen
Complex networks emerging in natural and human-made systems tend to assume small-world structure. Is there a common mechanism underlying their self-organisation? Our computational simulations show that network diffusion (traffic flow or information transfer) steers network evolution towards emergence of complex network structures. The emergence is effectuated through adaptive rewiring: progressive adaptation of structure to use, creating short-cuts where network diffusion is intensive while annihilating underused connections. With adaptive rewiring as the engine of universal small-worldness, overall diffusion rate tunes the systems' adaptation, biasing local or global connectivity patterns. Whereas the former leads to modularity, the latter provides a preferential attachment regime. As the latter sets in, the resulting small-world structures undergo a critical shift from modular (decentralised) to centralised ones. At the transition point, network structure is hierarchical, balancing modularity and centrality - a characteristic feature found in, for instance, the human brain.

Funding

This work was supported by an Odysseus grant from the Flemish Organisation of Science (F.W.O.) to Cees van Leeuwen.

History

Citation

Scientific Reports, 2017, 7 Article number: 13158

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Mathematics

Version

  • AM (Accepted Manuscript)

Published in

Scientific Reports

Publisher

Nature Publishing Group:

issn

2045-2322

eissn

2045-2322

Acceptance date

2017-09-08

Copyright date

2017

Available date

2018-02-19

Publisher version

https://www.nature.com/articles/s41598-017-12589-9

Notes

Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-017-12589-9

Language

en

Usage metrics

    University of Leicester Publications

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC