MATEC Web Conf.
Volume 71, 2016The International Conference on Computing and Precision Engineering (ICCPE 2015)
|Number of page(s)||4|
|Section||Computational and Mathematical Sciences|
|Published online||02 August 2016|
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
* Corresponding author: firstname.lastname@example.org
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
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.