Identification of Key Nodes Based on Integrating of Global and Local Information

摘要

Identification of key nodes is a significant issue in the research of complex networks such as communication networks, power networks, etc. Identifying key nodes of complex networks and protecting them in a targeted manner can improve the security of the network. The traditional key nodes identification algorithms only concern a one-sided characteristic of nodes, usually, a specific algorithm is only suitable for a specific type of network. In this paper, we propose an algorithm SDB based on the measure of the degree and betweenness, which represents both the local features and the global features. This algorithm integrates the degree and betweenness centrality through the connection strength between nodes, so as to calculate the importance values of nodes and rank them. We evaluate the network performance after node removal in terms of network susceptibility value and network efficiency decline rate etc. The experimental results show that our proposed SDB algorithm helps find key nodes effectively in various types of complex networks, such as communication, transportation, biological and artificially generated networks, etc. The network can be divided into multiple clusters faster after removing these key nodes, which seriously damages the network connection.