A SUFFICIENT CONDITION FOR CLASSIFIED NETWORKS TO POSSESS COMPLEX NETWORK FEATURES

(Communicated by Benedetto Piccoli) Abstract. We investigate network features for complex networks. A sufficient condition for the limiting random variable to possess the scale free property and the high clustering property is given. The uniqueness and existence of the limit of a sequence of degree distributions for the process is proved. The limiting degree distribution and a lower bound of the limiting clustering coefficient of the graph-valued Markov process are obtained as well. 1. Introduction. Networks appear in various systems in the world, a class of which is the random networks. During the past decades, scientists in different fields have done many different work [12, 8, 7, 11] and achieved a lot of empirical and simulative results on the various real-world random networks, such as social networks, biological networks, electronic communication networks etc. These results reveal tha