In this work, we investigate and compare centrality metrics on several datasets. Many real-world complex systems can be addressed using a graph-based analytical approach, where nodes represent the components of the system and edges are the interactions or relationships between them. Different systems such as communication networks and critical infrastructure are known to exhibit common characteristics in their behavior and structure. Infrastructure networks such as power girds, communication networks and natural gas are interdependent. These systems are usually coupled such that failures in one network can propagate and affect the entire system. The purpose of this analysis is to perform a metric analysis on synthetic infrastructure data. Our view of critical infrastructure systems holds that the function of each system, and especially continuity of that function, is of primary importance. In this work, we view an infrastructure as a collection of interconnected components that work together as a system to achieve a domain-specific function. The importance of a single component within an infrastructure system is based on how it contributes, which we assess with centrality metrics.
Anthony Smith, Kaleb Smith, and Alex J. Aved, "Automating intra-links and node analysis," Proc. SPIE 10652, Disruptive Technologies in Information Sciences, 106520C (Presented at SPIE Defense + Security: April 17, 2018; Published: 9 May 2018); https://doi.org/10.1117/12.2306673.
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