The Path-Star Transformation and its Effects on Complex Networks

TL;DR

This paper explores how transforming paths into stars or hubs in various complex network models significantly alters their topology, impacting properties like diameter and shortest path length, with potential applications in network optimization.

Contribution

It introduces the path-star transformation and analyzes its effects on different complex network models, revealing unexpected invariances and potential for network improvement.

Findings

Diameter and average shortest path length are minimally affected in Erdos-Renyi networks.

Path-star transformation can optimize network connectivity.

Transformations can create hubs without adding edges.

Abstract

A good deal of the connectivity of complex networks can be characterized in terms of their constituent paths and hubs. For instance, the Barab\'asi-Albert model is known to incorporate a significative number of hubs and relatively short paths. On the other hand, the Watts-Strogatz model is underlain by a long path and almost complete absence of hubs. The present work investigates how the topology of complex networks changes when a path is transformed into a star (or, for long paths, a hub). Such a transformation keeps the number of nodes and does not increase the number of edges in the network, but has potential for greatly changing the network topology. Several interesting results are reported with respect to Erdos-R\'enyi, Barab\'asi-Albert and Watts-Strogats models, including the unexpected finding that the diameter and average shortest path length of the former type of networks are little affected by the path-star transformation. In addition to providing insight about the organization of complex networks, such transformations are also potentially useful for improving specific aspects of the network connectivity, e.g. average shortest path length as required for expedite communication between nodes.