Robustness measurement of multiplex networks based on graph spectrum

Area of Science:

• Complex Systems Science
• Network Science
• Graph Theory

Background:

• Networks model relationships in complex systems using nodes and links.
• Multilayer networks represent interactions between multiple interconnected systems.
• Multiplex networks, a type of multilayer network, feature replaceable or dependent relationships across layers.

Purpose of the Study:

• To develop and evaluate robustness measures for various multiplex network types.
• To generalize natural connectivity from graph spectra for multiplex network analysis.
• To correlate network topology with system robustness.

Main Methods:

• Generalizing natural connectivity calculations from graph spectra.
• Analyzing robustness using spectral graph theory.
• Conducting experiments on both model and real-world multiplex networks.

Main Results:

• A close correlation was observed between multiplex network robustness and the natural connectivity of aggregated networks or layer intersections.
• The proposed indicators effectively measure or estimate multiplex network robustness based on individual layer topology.
• The study validates findings on both synthetic and empirical multiplex network data.

Conclusions:

• Natural connectivity serves as a reliable indicator for assessing the robustness of multiplex networks.
• The findings provide insights for designing and protecting interconnected complex systems.
• Understanding layer topology is crucial for predicting overall network resilience.