Research On Analysis And Application Of Community Property Evolvement Of Internet Macroscopic Topology

Nowadays internet has become one of hottest research spots for a long time since to some extent it has a significant influence on human behavior in modern society.As the community structure is an important feature in the practical complex network system, thus understanding the community structure is helpful to understand the network topology property better. And it is also valuable to study the formulation and evolvement of the network. As searching and analyzing the community structure is helpful for good acquaintance of network structure, and modeling the complex network with community structure is beneficial to analyze the effect of community structure on network properties and dynamic performance, therefore, analyzing and modeling of the complex network's community structure is a challenging and prospective area.In this thesis, internet macro topology structure and its community property are analyzed, based on a massive amount of data nearly 60 million provided by CAIDA(The Cooperative Association for Internet Data Analysis). The results are furthermore implemented on a typical student network. The tasks are as follows.Based on current research, after introducing main content and results of different sorts of topology analysis techniques respectively, the internet topology structure model is analyzed, and a qualitative comparison on various models is carried out. Then the detailed statistics of various internet topology properties on AS(Autonomous System) class is indicated. After that a further analysis on network connectivity property and power-law distribution property is given. The timing analysis of network representative topology eigenvalue is also made, followed by the statistics of node life cycle and analysis of its aging law. The main factors of maintaining the network connectivity and power-law are finally listed.Definition of community and its structure are specified. Then the evaluation system of the network community property is proposed for the first time, consist of modularity, node degree, clustering coefficient, hop distribution, betweenness distribution, rich-club connection property, community scale distribution, etc.A deep analysis on some common network community ordinary properties including regular network, random network, small-world network and scale-free network, etc, is made by modularity splitting curve, and by which a conclusion is drawn that the community is one of the basic properties of network. It is also suggested that the modularity is effected by the density of network, and then a deep analysis on the relationship of community structure and complex network is presented.On the basis of modularity index, by analysis and study of the internet maro topology structure's community property, it can be concluded that the modularity of the internet topology is centered around 0.40, which indicates that the internet topology is also a sort of network with community structure.By analyzing the cause of the formulation of the internet macro topology's community structure, it shows that Autonomous System from one community mostly belong to the same country or adjacent countries, which reveals that geographical factor is a key influencing factor in internet community structure formulation. The results of analysis on the country-level topology community structure shows us that the main country-level communities internet topology just correspond to the main continents, which again is the evidence of aforementioned geographical influencing theory.By comprehensive use of degree first selection mechanism and community scale first selection mechanism, a sort of internet topology evolvement model—CGeoPFP model, which has community structure and is built on geographical evolvement theory, is proposed. Then by applying network community property evaluation index, the evolvement analysis of the community generated from CGeoPFP model is given. Its study results shows that if the network generated from this model, its community scale's cumulative distribution and node degree distribution both satisfy power-law propertyRelevant studies show that most community networks have community structure. University student as an important part of society network, is also a vital society network cell. The study of university student society network is significant to cultivation of high-quality innovative talents in new era, formulation of university student's comprehensive quality, and development of the ideological and political education. This thesis presents a typical example in the society network-----student network. A student network topology model is built up, and a genetic algorithm and simulated annealing algorithm is utilized for model optimization, by which the student network growth's fractal characteristics and posture are analyzed. Finally, by utilizing community property evaluation index, the community property of student network is analyzed.