The impact of heterogeneous dependency strength on the robustness of multi-layer networks
Year: 2024
Type: article
Abstract: The representation of real-world complex systems using multi-layer networks has attracted significant research attention. However, the exploration of multi-layer networks with heterogeneous dependency strengths, reflecting node properties in complex systems more accurately, remains under explored. In this study, we extend the homogeneous dependency model to introduce degree-dependent heterogeneous dependency strengths: degree-positive and degree-negative. This establishes a theoretical framework for multi-layer networks with heterogeneous dependency strengths, which are based on node attributes. We derive accurate equations for simulating percolation processes in these networks and confirm the results through computational experiments. Comparative analysis of percolation phase transitions and the resilience of dependent layers under random attacks reveals distinct characteristics of this model, enhancing understanding of real-world complex systems. Our findings provide theoretical insights for designing resilient multi-layer networks with heterogeneous dependency strengths, better reflecting the complexities of real-world systems. • Propose degree-dependent heterogeneous dependency strengths in multilayer networks. • Get critical points for continuous and discontinuous phase transitions analytically. • Compare robustness under homogeneous versus heterogeneous dependency strengths.
Source: Chaos Solitons & Fractals
Authors: Chaoyang Zhang, Liang Gao, J.F.F. Mendes
Institutions: Beijing Jiaotong University, University of Aveiro
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
OpenAlex ID: W4405122246