Bursty Switching Dynamics Promotes the Collapse of Network Topologies

TL;DR

This paper introduces a continuous-time switching topology model driven by bursty behavior to study how dynamic connections influence network structure and processes, revealing that switching can lead to topology collapse and affect network functions.

Contribution

It presents a novel bursty switching model for temporal networks and analyzes its impact on network topology and dynamics using Markov chain theory.

Findings

Switching dynamics can cause network topology collapse.

Bursty switching reduces network heterogeneity.

Switching influences random walks and promotes cooperation.

Abstract

Time-varying connections are crucial in understanding the structures and dynamics of complex networks. In this paper, we propose a continuous-time switching topology model for temporal networks that is driven by bursty behavior and study the effects on network structure and dynamic processes. Each edge can switch between an active and a dormant state, leading to intermittent activation patterns that are characterized by a renewal process. We analyze the stationarity of the network activation scale and emerging degree distributions by means of the Markov chain theory. We show that switching dynamics can promote the collapse of network topologies by reducing heterogeneities and forming isolated components in the underlying network. Our results indicate that switching topologies can significantly influence random walks in different networks and promote cooperation in donation games. Our research thus provides a simple quantitative framework to study network dynamics with temporal and intermittent interactions across social and technological networks.