中心性
脆弱性
计算机科学
复杂网络
弹性(材料科学)
优势(遗传学)
网络拓扑
网络科学
节点(物理)
分布式计算
拓扑(电路)
计算机网络
工程类
数学
生物
生物化学
化学
物理
电气工程
结构工程
物理化学
组合数学
万维网
基因
热力学
作者
Marcus Engsig,Alejandro Tejedor,Yamir Moreno,Efi Foufoula‐Georgiou,Chaouki Kasmi
标识
DOI:10.1038/s41467-023-44257-0
摘要
Abstract Determining the key elements of interconnected infrastructure and complex systems is paramount to ensure system functionality and integrity. This work quantifies the dominance of the networks’ nodes in their respective neighborhoods, introducing a centrality metric, DomiRank, that integrates local and global topological information via a tunable parameter. We present an analytical formula and an efficient parallelizable algorithm for DomiRank centrality, making it applicable to massive networks. From the networks’ structure and function perspective, nodes with high values of DomiRank highlight fragile neighborhoods whose integrity and functionality are highly dependent on those dominant nodes. Underscoring this relation between dominance and fragility, we show that DomiRank systematically outperforms other centrality metrics in generating targeted attacks that effectively compromise network structure and disrupt its functionality for synthetic and real-world topologies. Moreover, we show that DomiRank-based attacks inflict more enduring damage in the network, hindering its ability to rebound and, thus, impairing system resilience. DomiRank centrality capitalizes on the competition mechanism embedded in its definition to expose the fragility of networks, paving the way to design strategies to mitigate vulnerability and enhance the resilience of critical infrastructures.
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