Deterministic Networks And Synchronizability Optimization In Complex Network

This thesis has mainly made contribution to the areas of complex network model and the optimization in synchronability of complex networks. By observing the local characters of network models and the statistic characteristics of random small-world network, scale-free network, deterministic small-world network and deterministic scale-free network, we found that there exists a common disadvantage among almost all existing algorithms for generating deterministic network:they all run in an iterative way and generate networks with only several discrete number of nodes. According to these facts, this paper proposes a deterministic network generation algorithm, which can not only generate deterministic networks following a scale-free distribution of degree and small-world behavior, but also produce networks with arbitrary number of nodes. According to these facts, we propose a deterministic network generation algorithm, which can not only generate deterministic networks following a scale-free distribution of degree and small-world behavior, but also produce networks with arbitrary number of nodes. Analytical computation and simulation results have proved the above statements, and the experiments of random walk have shown that the proposed network has a strong ability for information spreading. Besides this, we also explored the field of synchronization of complex network and proposed a algorithm for optimizing the synchronizability of networks, which lays foundation for future applications.