A novel deterministic hybrid complex network model created by inner-outer iteration

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作者单位: a College of Information and Engineering, Taishan Medical University, Taian 271016, China Institute of Neuroinformatics, Dalian University of Technology, Dalian 116023, China

摘要: Complex networks are ubiquitous in reallife systems. Most previous models of complex networks are stochastic. In order to decrease the randomness and make it more direct to gain a visual understanding on complex network evolving mechanism, we present a deterministic algorithm that generates a hybrid network model with the characteristics of small-world networks and random networks. In this model, the network growth is determined by triangle inner and outer node and edge iterations. We analyze th...更多; Complex networks are ubiquitous in reallife systems. Most previous models of complex networks are stochastic. In order to decrease the randomness and make it more direct to gain a visual understanding on complex network evolving mechanism, we present a deterministic algorithm that generates a hybrid network model with the characteristics of small-world networks and random networks. In this model, the network growth is determined by triangle inner and outer node and edge iterations. We analyze the main topological properties by both theoretical predictions and numerical simulations. The results show that our growing model has a low average path length, a high clustering and an exponential degree distribution.收起

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