Simulation Software For Visualization Of Complex Networks

With many complex systems can be abstracted the study of complex network, complex network has become a hot research topic. However, due to the structure of complex network is abstract and complex, it is difficult to visually display the topology with traditional text or data tables, some of the key information is concealed. Meanwhile, research-scale of complex network has undergone tremendous changes, from the initial small network of hundreds of nodes into a now thousands or even millions of nodes on a large network, thus the requirement to provide simulation softwares to simulate the topology and dynamic behavior of complex network is very urgent.Firstly, the existing simulation softwares, topological parameters and applications of complex network are analyzed and summarized, and then the functional framework of visual simulation software of complex network is designed. Based on consideration of software reuse and time complexity of the algorithm, the simulation software utilizes Igraph to create logical structure of complex network with given type and parameters, and visualization is completed by MFC double buffering technology and layout algorithms. In addition, the simulation software uses classical algorithms to provide APIs of many important topological parameters, and can support many data file formats of complex network, such as GML, GraphML and so on, thus facilitating the use of the existing complex network data.The study of this paper involves the basic theory of complex network, information visualization, and other fields, combining Igraph and MFC to implement a visual simulation software of complex network. In addition, this paper also uses the simulation software to simulate an algorithm for improving complex network capacity based on betweenness centrality. Simulation results show that the simulation software not only facilitates the construction of complex network and access to related topological parameters, but also provides appropriate support to simplify the implementation of simulation algorithms, thus enabling researchers to better focus on the nature of problems in their research areas.