Improving the robustness of complex networks with preserving community structure

Area of Science:

• Network Science
• Complex Systems Analysis
• Cybersecurity

Background:

• Complex networks, such as power grids and airline systems, exhibit 'robust yet fragile' properties, being resilient to random failures but vulnerable to targeted attacks.
• Cascading failures and malicious attacks on these networks pose significant risks, necessitating improved robustness strategies.
• Existing robustness enhancement methods often overlook the preservation of community structure, a critical characteristic defining network functionality.

Purpose of the Study:

• To investigate the relationship between network robustness and community structure.
• To propose a novel strategy for improving network robustness while preserving both community structure and degree distribution.
• To provide a framework for designing and integrating more resilient complex networks.

Main Methods:

• A 3-step strategy was developed to enhance network robustness.
• The strategy focuses on preserving the community structure and degree distribution of the networks.
• Extensive experimentation was conducted on real-world network datasets.

Main Results:

• The proposed method significantly improves network robustness.
• The strategy effectively preserves the community structure of the networks.
• The degree distribution of the networks was successfully maintained throughout the process.

Conclusions:

• The developed 3-step strategy is effective in enhancing the robustness of complex networks.
• Preserving community structure is crucial for maintaining network functionality alongside robustness.
• The findings offer valuable insights for designing and improving the resilience of critical infrastructure networks.