Title :
High Clustering Coefficient of Computer Networks
Author_Institution :
Coll. of Math. & Comput. Sci., China Univ. of Pet., Dongying, China
Abstract :
Due to the rapid development of network technology, the structure of computer network is increasingly complicated.The traditional random network model is difficult to characterize the topology of current computer network.Complex network theory provides new view and thinking to study in this field. In this paper, we give a probabilistic model to examine the evolution of computer networks by random duplication processes of node degree as well as the preferential choice mechanisms. The model is solved exactly for large network. We demonstrate that both the degree distribution and the triangle distribution have stationary properties. When the size of the network tends to infinity,the degree distribution behaves as P(k) prop k-3 and the average clustering coefficient C is independent of the network size N.
Keywords :
computer networks; probability; random processes; statistical analysis; telecommunication network topology; computer network clustering coefficient; computer network topology; degree distribution; network technology; network theory; probabilistic model; random duplication process; triangle distribution; Complex networks; Computational modeling; Computer networks; Educational institutions; H infinity control; Mathematics; Network topology; Numerical simulation; Petroleum; Predictive models;
Conference_Titel :
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location :
Taiyuan, Shanxi
Print_ISBN :
978-0-7695-3679-8
DOI :
10.1109/ICIE.2009.276