DocumentCode :
550548
Title :
Weighted scale-free network with widely weighted dynamics
Author :
Mu Junfen ; Sun Hexu ; Pan Jiaping ; Zhou Jin
Author_Institution :
Sch. of Electr. Eng. & Autom., Hebei Univ. of Technol., Tianjin, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
904
Lastpage :
909
Abstract :
This brief paper formulates and studies a simple yet general weighted evolving network model. In contrast with the well-known Barrat-Barthélemy-Vespignani (BBV) locally weighted evolving model, this model can allow the flows to be widely updated. We provide both analysis and simulation of the network characteristics for such weighted model, and all the theoretical predictions are successfully contrasted with numerical simulations. It is shown that this model recovers three power-law distributions for the node degrees, connection weights and node strengths, respectively. Also, the droop-head and heavy-tail properties of these distributions, which are observed in many real-world networks, can be reflected by the present model. Furthermore, it turns out that the strength highly correlates with the degree and displays a scale-free behavior as confirmed by empirical evidence.
Keywords :
complex networks; network theory (graphs); probability; connection weight; droop head properties; heavy tail properties; network characteristics; node degrees; node strength; power law distribution; weighted evolving network model; weighted scale-free network; Analytical models; Complex networks; Computational modeling; Mathematical model; Numerical models; Predictive models; Probability distribution; BBV Model; Complex Networks; Scale-free Networks; Weighted Dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000887
Link To Document :
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