Local-world and cluster-growing weighted networks with controllable clustering

Chun-Xia Yang (), Min-Xuan Tang (), Hai-Qiang Tang () and Qiang-Qiang Deng ()
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Chun-Xia Yang: School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China
Min-Xuan Tang: School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China
Hai-Qiang Tang: School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China
Qiang-Qiang Deng: School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China

International Journal of Modern Physics C (IJMPC), 2014, vol. 25, issue 05, 1-12

Abstract: We constructed an improved weighted network model by introducing local-world selection mechanism and triangle coupling mechanism based on the traditional BBV model. The model gives power-law distributions of degree, strength and edge weight and presents the linear relationship both between the degree and strength and between the degree and the clustering coefficient. Particularly, the model is equipped with an ability to accelerate the speed increase of strength exceeding that of degree. Besides, the model is more sound and efficient in tuning clustering coefficient than the original BBV model. Finally, based on our improved model, we analyze the virus spread process and find that reducing the size of local-world has a great inhibited effect on virus spread.

Keywords: Complex networks; local-world; power-law distribution; tunable clustering coefficient; 89.75.-k; 89.75.Fb; 89.75.Hc; 89.65.-s (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0129183114400099

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