Approach to network failure due to intrinsic fluctuations

Area of Science:

• Network science
• Statistical physics
• Complex systems

Background:

• Understanding network resilience is crucial for infrastructure stability.
• Intrinsic fluctuations can lead to unexpected system failures.
• Previous models often overlook the impact of internal dynamics on network collapse.

Purpose of the Study:

• To investigate network failure caused solely by internal flux fluctuations.
• To identify distinct regimes of nodal failure preceding complete network collapse.
• To analyze the universality of these failure mechanisms across different network topologies.

Main Methods:

• Modeling node flux as random walkers.
• Characterizing large fluctuations as extreme events leading to node failure.
• Analyzing failure progression in various network models (square lattice, all-to-all, scale-free, Erdos-Renyi).
• Developing an analytical approximation for all-to-all networks.

Main Results:

• Three distinct nodal failure regimes were identified before complete network failure.
• The approach to network failure showed qualitative similarity across diverse network types.
• An approximate analytical description for the failure approach in all-to-all networks was derived.
• The failure scenario was validated using a real-world flight transportation network.

Conclusions:

• Intrinsic flux fluctuations are a significant driver of network failure.
• A universal three-regime failure process exists in many network types.
• The findings provide a framework for understanding and predicting network resilience based on internal dynamics.