Research On The Relationships Of The Structure And Function In Complex Networks Based On Search Efficiency

Complex network theory is of great benefit to the research such as the dissemination and sharing of information, game and income of community, control the dynamic behavior of objects. Exploring the structure and function of complex networks has become a key of the network science. Given the diversity of complex network topology and function,the thesis selected ubiquitous search function for the study, to explore the relationship between complex network structure and search function. It is of great significance to the discovery of the actual network evolution model, understanding cooperative relations among societies, searching the Internet and social network analysis.Firstly, the thesis introduces the related basic concepts and research status of complex networks in order to point out that, ER random graph network, WS small-world network and BA scale-free networks are three classic complex network topologies at present recognized by experts. Studying the relationship between these models andthe search function has important implications for pervasive network science. Secondly, it gives a simple analysis for the basic theory of the structure and functions in the field such as philosophy, sociology and complex network. Thirdly, this thesis presents "the competition evolution guess of complex network"earlier and confirms this conjecture in a fairer heterogeneous network model based on the search efficiency, which explains the reason that ubiquitous scale-free characteristics of the structure in the real complex networks to some extent and explains the relationship between scale-free structure and search function. This study shows that, a network model with scale-free property is more conducive to search than other models. The experiments has found asymmetries in search and the search results show that the path length of the search of the BA network can be up to 7 times to the WS network, and have observed this phenomenon further in a number of actual non-sequential network. However, the competition process of real network can only be observed from the evolution of the sequential network. Finally,the thesis selects DBLP sequential network as a target and analyzes the structural model and the role position of it and dissects the law of subnet scale evolution over time deeply.The results prove the existence of a large number of complex heterogeneous local communities in the real network evolution, and the subnets with scale-free nature grow fastest so that they have obvious advantages. This work enrich the previous research results for complex networks in the field in a certain extent and helps to find means with practical value to optimize search efficiency or the disseminating information. It has made up for difficulty brings to the searching from the global topologies lack of complex network, and also promotes verification and analysis of structure and function theory in large and complex networks.