  In this paper, we propose an evolving network model growing fast in units of
module, based on the analysis of the evolution characteristics in real complex
networks. Each module is a small-world network containing several
interconnected nodes, and the nodes between the modules are linked by
preferential attachment on degree of nodes. We study the modularity measure of
the proposed model, which can be adjusted by changing ratio of the number of
inner-module edges and the number of inter-module edges. Based on the mean
field theory, we develop an analytical function of the degree distribution,
which is verified by a numerical example and indicates that the degree
distribution shows characteristics of the small-world network and the
scale-free network distinctly at different segments. The clustering coefficient
and the average path length of the network are simulated numerically,
indicating that the network shows the small-world property and is affected
little by the randomness of the new module.
