Research on Dynamic Evolution Model and Method of Communication Network Based on Real War Game

Area of Science:

• Systems Engineering
• Network Science
• Military Technology

Background:

• Combat systems rely on interconnected platforms for information sharing and collaborative processing.
• Existing combat system generation algorithms are often too simplistic for real-world applications.
• Effective communication networks are crucial for the functionality of combat System-of-Systems.

Purpose of the Study:

• To develop a more realistic and effective communication network generation algorithm for combat systems.
• To address the limitations of current algorithms in modeling complex combat environments.
• To enhance the resilience and performance of combat networks under attack.

Main Methods:

• Proposed a novel communication network generation algorithm using a joint distribution strategy.
• Combined power law distribution and Poisson distribution to model the communication network.
• Employed simulation methods to analyze network performance under continuous attack on communication nodes.

Main Results:

• The proposed algorithm effectively models communication networks in combat scenarios.
• Simulations demonstrated the network's operation and resilience under continuous attack.
• Experimental results validated the rationality and effectiveness of the communication network construction.

Conclusions:

• The developed algorithm provides a more realistic approach to combat network generation.
• The findings support the use of this model for designing robust combat System-of-Systems.
• The research contributes to improving information collection, sharing, and collaborative processing in military operations.