Title :
A novel evolving network model 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
Abstract :
It is well known that in Barrat-Barthélemy-Vespignani (BBV) model, the rearrangement of weights is local. In this paper, we present a novel weighted evolving network model that allows the flows to be widely updated. This model gives power-law distributions of degree, weight and strength, as confirmed in many real networks. Particularly, the exponents are nonuniversal and depend on a parameter that controls the total weight growth of the network. And it is shown that the droop-head and heavy-tail properties of these distributions, which are observed in many real-world networks, can be reflected by this new network model. It turns out that the strength highly correlates with the degree and displays scale-free property, which is in consistence with empirical evidence. Simulations are provided to demonstrate the theoretical results.
Keywords :
complex networks; graph theory; large-scale systems; statistical distributions; Barrat Barthelemy Vespignani model; evolving network model; power law distribution; widely weighted dynamics; Airports; Analytical models; Atmospheric modeling; Biological system modeling; Complex networks; Mathematical model; Numerical models; BBV model; Complex networks; Power-law distributions; Weighted evolving network; Widely weighted dynamics;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554063