A novel scale-free network model based on clique growth

A novel scale-free network model based on clique (complete subgraph of random size) growth and preferential attachment was proposed. The simulations of this model were carried out. And the necessity of two evolving mechanisms of the model was verified. According to the mean-field theory, the degree distribution of this model was analyzed and computed. The degree distribution function of vertices of the generating network P(d) is 2m(2)m(1)(-3) (d-m(1)+1)(-3), where m and m(1) denote the number of the new adding edges and the vertex number of the cliques respectively, d is the degree of the vertex, while one of cliques P(k) is 2m(2)k(-3), where k is the degree of the clique. The simulated and analytical results show that both the degree distributions of vertices and cliques follow the scale-free power-law distribution. The scale-free property of this model disappears in the absence of any one of the evolving mechanisms. Moreover, the randomicity of this model increases with the increment of the vertex number of the cliques.