Optimization of robustness of interdependent network controllability by redundant design

Area of Science:

• Complex network theory
• Network science
• Systems engineering

Background:

• Interdependent networks are coupled systems susceptible to cascading failures.
• Controllability of these networks is crucial but often compromised by failures.
• Optimizing the robustness of interdependent network controllability is a significant challenge.

Purpose of the Study:

• To analyze the cascading process in interdependent networks under node attacks.
• To measure and analyze the robustness of network controllability.
• To propose and evaluate strategies for optimizing controllability robustness.

Main Methods:

• Constructing a model of interdependent networks.
• Simulating cascading processes under varying proportions of node attacks.
• Measuring structural controllability using minimum driver nodes.
• Proposing a novel parameter to analyze robustness.
• Implementing and comparing redundant design strategies (node backup, edge backup) with cost considerations.

Main Results:

• Node backup and redundancy edge backup effectively reduce node failures and enhance controllability robustness.
• Specific strategies like Betweenness-Based Strategy (BBS) or Degree-Based Strategy (DBS) for node backup and High Degree First (HDF) for edge backup are identified as cost-effective.
• The proposed strategies demonstrate feasibility and effectiveness in improving network controllability.

Conclusions:

• Redundant design is a viable approach to bolster the controllability of interdependent complex networks.
• Tailoring backup strategies based on network structure and cost is essential for optimal robustness.
• The findings provide practical guidelines for enhancing the resilience of real-world complex systems.