Overload-based cascades on multiplex networks and effects of inter-similarity

Area of Science:

• Network Science
• Complex Systems
• Systems Engineering

Background:

• Cascading failures in interdependent networks are a growing concern.
• The impact of overlapping links (inter-similarity) on network robustness remains poorly understood.
• Shared links are prevalent in real-world coupled systems like traffic networks.

Purpose of the Study:

• To develop a novel model for load-based cascading failures in multiplex networks.
• To systematically investigate the influence of inter-similarity on system robustness.
• To compare the effects of different network structures, coupling schemes, and overload rules.

Main Methods:

• Proposed a new model for load-based cascading failures in multiplex networks.
• Compared various network structures, coupling schemes, and overload rules.
• Systematically analyzed the impact of inter-similarity on robustness under intentional attacks.

Main Results:

• Inter-similarity can negatively impact the robustness of coupled networks to overload cascades.
• Identified a competition between positive and negative effects of overlapping links on network robustness.
• Demonstrated that overlapping links do not always enhance resilience.

Conclusions:

• The presence of overlapping links in coupled networks can paradoxically reduce overall robustness.
• Understanding the nuanced role of inter-similarity is crucial for designing resilient complex systems.
• Findings offer practical guidance for enhancing the robustness of coupled traffic systems.