Recovery of Interdependent Networks

Area of Science:

• Network Science
• Complex Systems
• Statistical Physics

Background:

• Cascading failures in interdependent networks pose significant risks to system stability.
• Existing research primarily addresses failure preconditions, neglecting system recovery strategies.
• The challenge lies in developing effective methods to repair failing systems before complete breakdown.

Purpose of the Study:

• To introduce and analyze a novel node recovery strategy for interdependent networks.
• To develop a framework for studying concurrent failure and recovery dynamics.
• To identify critical recovery thresholds that prevent system collapse.

Main Methods:

• Developing an efficient and practical node recovery strategy targeting neighbors of the largest connected component.
• Employing analytic and numerical methods to study system behavior under concurrent failure and recovery.
• Analyzing the phase diagram in the recovery probability (γ) versus initial failure fraction (1-p) plane.

Main Results:

• A critical recovery probability (γ) was identified, determining system fate for a given initial failure (1-p).
• Above this critical probability, the system fully restores; below it, abrupt collapse occurs.
• Three distinct phases were observed in the γ-p phase diagram: no collapse, recovery-induced restoration, and unavoidable collapse.

Conclusions:

• The proposed recovery strategy is effective in preventing cascading failures in interdependent networks.
• System resilience is critically dependent on the interplay between initial failure extent and recovery probability.
• The findings provide crucial insights for designing robust and repairable complex network systems.