Key Node Identification Algorithm of Complex Network Based on Degree and Betweenness of Medium Centrality
The identification of key nodes in complex networks has always been a hot topic in complex network research.Re-searchers propose a variety of key node identification algorithms based on local or global attributes of the network.The traditional key node identification algorithm only considers the influence of single factor such as degree centrality or betweenness centrality,which has some limitations.Network entropy is an important index to measure the amount of information carried by the network.Ac-cording to the degree centrality and betweenness centrality of the network,this paper defines the betweenness centrality,and com-bines with the network entropy,and proposes a centrality algorithm based on the local and global attributes of the network.The invul-nerability of network is compared with degree centrality,betweenness centrality,local entropy and mapping entropy.Simulation re-sults show that compared with the other four algorithms,the key nodes identified by the entropy algorithm can make the network con-nectivity drop to the collapse threshold faster,and can identify the key nodes more accurately.At the same time,it is verified in real network,and it is found that the performance of mesocentricity entropy algorithm is better in real network.
degree-betweenness of medium centralitykey nodesdegree centralitybetweenness centralitydestructibility
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