Research on the Methods of Identifying Key Node Based on Classical Networks

• Published in: Applied Mechanics and Materials Vol. 530-531; no. Advances in Measurements and Information Technologies; pp. 489 - 495
• Main Author: Wang, Song Hua
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.02.2014
• Subjects: Computer simulation; Decomposition; Hot spots; Networks; Key Node; Classical Network Model; SIR Propagation Model
• ISBN: 3038350397; 9783038350392
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.530-531.489

Identifying the most important node is a research hotspot in complex networks. For different types of network there are different methods to cope with. In this paper, we use five methods: degree method, betweenness method, node contraction method, node importance evaluation matrix method, K-shell decomposition method to identify the key node and compare the effects through SIR propagation model. In the simulation experiments, we use three artificial networks: random network (ER), small-world network (NW) and scale-free network (BA). The experimental results show that the nodes identified by node importance evaluation matrix method and K-shell method are more important. Besides, in BA the infection velocity is faster and the infection scale is larger than in ER and NW.