Critical nodes identification based on comprehensive topological importance in complex networks

Peizhe Li, Linjin Xie, Yefan Wu, Haotian Liu, Yong Wang, Jianhan Zhou, Xiaoping Wu, Lilin Qiao, Quanbiao An, Siyu Yang
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Abstract

The identification of critical nodes in the network is of great significance for the research of the invulnerability and structural stability of complex networks. Most of the existing studies evaluate the importance of nodes in networks from a single structural perspective. Considering the local and global characteristics of the network, an identification algorithm of critical nodes in complex networks based on comprehensive topological importance (CTI) is proposed. The algorithm uses the theory of multiple attribute decision making (MADM) to quantitatively analyze the influence of different attributes on nodes and determine the comprehensive topology importance of nodes, which represents their structural importance in complex networks. Based on two simulation networks and five classical real networks, the proposed algorithm is proved to be superior to DC, LLS, P and WL indexes based on local information and BC indexes based on global information through the change of network efficiency under critical nodes attacking.
复杂网络中基于综合拓扑重要性的关键节点识别
网络中关键节点的识别对于研究复杂网络的抗灾性和结构稳定性具有重要意义。现有的研究大多是从单一结构的角度来评估网络中节点的重要性。考虑到网络的局部和全局特性,提出了一种基于综合拓扑重要性(CTI)的复杂网络关键节点识别算法。该算法利用多属性决策(MADM)理论,定量分析不同属性对节点的影响,确定节点的综合拓扑重要度,代表节点在复杂网络中的结构重要度。基于两个仿真网络和五个经典真实网络,通过关键节点攻击下网络效率的变化,证明了该算法优于基于局部信息的DC、LLS、P和WL指标和基于全局信息的BC指标。
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