1. School of Mechanics and Civil Engineering, China University of Mining & Technology, Beijing 100083, China;
2. School of Accounting and Finance, Zhejiang Business College, Hangzhou 310053, China;
3. School of Science, Heilongjiang University of Science and Technology, Harbin 150022, China
Abstract：Three typical complex network models and corresponding traffic routing models were established to carry out numerical computation and simulation of topological indicators and network capacity, and empirical analysis of how network capacity is influenced by network topology was conducted. The results show that numerical calculation results and experimental results of the capacity of three different networks were roughly consistent. With existence of the core node, scale-free network had the shortest average travel path, and the proportion of the largest betweenness was much higher than that in other networks, leading to minimum capacity of the scale-free network; the proportion of the largest betweenness of nodes in random network was lower than that in other networks, leading to maximum capacity of the random network. The increase of average degree resulted in significant increase of network capacity, but the contribution of different topological indicators was not the same. Understanding the quantitative relation between network topology and network capacity is beneficial to conducting effective prevention and intervention concerning dynamic processes in the network.
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2015, Vol. 33 
