Random Networks

Complex networks describe a variety of systems found in nature and society. Traditionally these systems have been modelled as random graphs, a relatively primitive and brutal approach. These traditional models do not produce topological and structural properties featured in real network examples. In recent years many new models have been developed, to correctly describe the scale – free structure of real networks. In this papers the real world networks (WWW, Internet, ecological, cellular, etc.) are presented along with various theoretical models, that explain the emergence of the most important structural properties as average path length, clustering coefficient and power – tail degree distributions. In the end of the paper the basics of network evolution process is explained.