Interdependent networks with identical degrees of mutually dependent nodes.
Sergey V Buldyrev1, Nathaniel W Shere, Gabriel A Cwilich
1Department of Physics, Yeshiva University, 500 West 185th Street, New York, New York 10033, USA.
Summary
We analyzed interdependent networks with identical node degrees, finding that these correspondently coupled networks (CCNs) exhibit enhanced robustness against random node failures compared to standard coupled networks.
Area of Science:
- Network Science
- Statistical Physics
- Complex Systems
Background:
- Interdependent networks are crucial in various systems, but their failure dynamics are complex.
- Previous studies on coupled networks often assume independent degree distributions.
- Understanding the resilience of networks with synchronized dependencies is vital.
Purpose of the Study:
- To investigate the failure dynamics of two interdependent networks with identical node degrees.
- To introduce and analyze the properties of correspondently coupled networks (CCNs).
- To determine the conditions for percolation transitions and system robustness in CCNs.
Main Methods:
- Analytical derivation of the fraction of nodes in the mutual giant component.
- Analysis of percolation transitions based on arbitrary degree distributions P(k).
- Examination of first-order and second-order transitions for different network types, including scale-free networks.
Main Results:
- Correspondently coupled networks (CCNs) exhibit a lower percolation threshold (p(c)) than randomly coupled networks.
- A first-order transition occurs if the degree distribution's second moment is finite.
- Scale-free networks with 2<λ≤3 show a second-order transition, with p(c)=0 for λ<3.
Conclusions:
- CCNs demonstrate increased robustness against random failures due to synchronized dependencies.
- The broadness of the degree distribution positively correlates with the robustness of CCNs.
- The findings provide insights into designing more resilient interdependent network systems.
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