Comprehensive Weighted Clique Degree Ranking Algorithms and Evolutionary Model of Complex Network
Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), School of Communication and Information Engineering, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, Chengdu 622731, China
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This paper analyses the degree ranking (DR) algorithm, and proposes a new comprehensive weighted clique degree ranking (CWCDR) algorithms for ranking importance of nodes in complex network. Simulation results show that CWCDR algorithms not only can overcome the limitation of degree ranking algorithm, but also can find important nodes in complex networks more precisely and effectively. To the shortage of small-world model and BA model, this paper proposes an evolutionary model of complex network based on CWCDR algorithms, named CWCDR model. Simulation results show that the CWCDR model accords with power-law distribution. And compare with the BA model, this model has better average shortest path length, and clustering coefficient. Therefore, the CWCDR model is more consistent with the real network.
© The Authors, published by EDP Sciences, 2016
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