DocumentCode :
2665946
Title :
Dynamical evolution of weighted scale-free network models
Author :
Wang, Dan ; Qian, Xiaolong ; Jin, Xiaozheng
Author_Institution :
Key Lab. of Manuf. Ind. Integrated Autom., Shenyang Univ., Shenyang, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
479
Lastpage :
482
Abstract :
Inspired by the weighted network model proposed by Barrat, Barthélemy, and Vespignani (BBV), we construct a new evolving model that characterizes the weighted scale-free networks with community structure by adjusting one parameter. In the process of the evolution, a new node or a new community with a probability is added to the network, and new links are added to the network according to the strength preferential attachment rule. Theoretical analyses and numerical simulations show that our model captures power-law distributions of node strengths and link weights, as confirmed in several real-world systems.
Keywords :
complex networks; network theory (graphs); numerical analysis; probability; community structure; dynamical evolution; evolving model; link weights; node strengths; numerical simulations; power-law distributions; probability; real-world systems; strength preferential attachment rule; theoretical analyses; weighted scale-free network models; Biological system modeling; Communities; Complex networks; Educational institutions; Numerical models; Topology; Scale-free network; Weighted network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6244073
Filename :
6244073
Link To Document :
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