A biophysical approach to the design of networks of communication systems

TL;DR

This paper introduces a biophysical modeling approach inspired by Physarum polycephalum to design efficient communication networks, demonstrated through application to the Portuguese railway system.

Contribution

It develops a formalism for adaptive flow-based network design inspired by biological growth, enabling the creation of near-optimal or Steiner-like network configurations.

Findings

Identifies network graphs that are optimal or suboptimal in length.

Derives Steiner tree configurations topologically.

Successfully applies the method to real-world railway network data.

Abstract

Inspired by the growth dynamics of the protist \textit{Physarum polycephalum}, we employ a formalism that describes adaptive, incompressible Hagen-Poiseuille flows on channel networks to identify graphs connecting different nodes within Euclidean space. These graphs are either suboptimal or optimal with respect to their length. Occasionally, we derive graph tree configurations that are topologically equivalent to Steiner trees. This methodology can be utilised to assist in making decisions regarding the design of communication networks, such as fibre webs, motorways, or railway networks. As a demonstration of the practicality of this approach, we explicitly apply this framework to the Portuguese railway network.