Vital node identification based on cycle structure in a multiplex network.

Area of Science:

• Complex systems science
• Network science
• Epidemiology

Background:

• Multiplex networks represent real-world systems with nodes having multiple functional and structural roles.
• Identifying vital nodes is essential for network control, such as managing pandemic outbreaks (e.g., COVID-19), mitigating cyber-attacks, and ensuring traffic flow.

Purpose of the Study:

• To propose novel indexes for identifying vital nodes in multiplex networks.
• To evaluate the effectiveness of these new indexes compared to existing methods.

Main Methods:

• Development of hybrid supra-cycle number and hybrid supra-cycle ratio indexes based on network cycle structure.
• Extensive experimental analysis comparing proposed indexes with several existing indexes on four real-world multiplex networks.
• Evaluation of performance on both layer nodes and multiplex nodes.

Main Results:

• The proposed hybrid supra-cycle indexes demonstrate good robustness and synchronization capabilities.
• The indexes effectively capture transmission dynamics within multiplex networks.
• Experimental results confirm the superiority of the proposed indexes in vital node identification.

Conclusions:

• The novel cycle-based indexes provide an effective approach for vital node identification in multiplex networks.
• These findings enhance the understanding of multiplex network structures and cycle dynamics.
• The proposed methods offer valuable tools for network control and resilience strategies.