Robustness and Statistical Characters of a Class of Complex Network Models

A class of dynamic complex network evolving models with multitriangular structure is given. By utilizing the mean-field theory, it is proved that the models have the probability of power-law degree distribution with large average coefficient clusters. Then, by MATLAB tools, robustness of the models is analyzed according to two attacking strategies: random attack and max-degree attack. The results show that the robustness of the models are similar as that of the BA models at random attack, but the models are more vulnerable than that of the BA models at max-degree attack. © 2012 Springer-Verlag Berlin Heidelberg.