The space information networks (SIN) have a series of characteristics, such as strong heterogeneity, multiple types of resources, and difficulty in management. Aiming at the problem of resource allocation in SIN, this paper firstly establishes a hierarchical and domain-controlled SIN architecture based on software-defined networking (SDN). On this basis, the transmission, caching, and computing resources of the whole network are managed uniformly. The Asynchronous Advantage Actor-Critic (A3C) algorithm in deep reinforcement learning is introduced to model the process of resource allocation. The simulation results show that the proposed scheme can effectively improve the expected benefits of unit resources and improve the resource utilization efficiency of the SIN.

Aiming at the complex structure of the space information networks (SIN) and the dynamic change of network topology, in order to design an efficient routing strategy, this paper establishes a SIN management architecture based on Software-defined Networking (SDN). A routing algorithm flow of the spatial information network based on a snapshot sequence is designed. For different spatial tasks with different Quality of Service (QoS) requirements, the concept of integrated link weight is proposed. The Warshall–Floyd algorithm is used to design the optimal routing strategy. A Task-oriented Bandwidth Resource Allocation (TBA) algorithm is proposed for multiple spatial tasks in the same link. Simulation results show that the algorithm can effectively guarantee the priority transmission of important tasks and avoid the unnecessary waste of bandwidth resources.

Network visualization is a time-honored research direction, which can be traced back to the graph visualization. The data of dynamic network is constantly updated, which brings some challenges to dynamic network visualization. Dynamic network visualization mainly includes network layout, network property visualization and user interaction, therefore, this paper focuses on the research and review of some key technologies, including layout technology, visualization technology and interactive technology. The aim of this paper is to provide some technical support for the research of the key technology of dynamic network visualization.

As an important national strategy infrastructure, the Space Information Network (SIN) is a powerful platform for future information support, and it plays an important role in many aspects such as national defense, people’s livelihood, etc. In this paper, we review typical and mainstream topology evolution models in different periods, and analyze the demand for studying the dynamic evolution model of SIN. Combining the concept and characteristics, we analyze the topology structure and local-world phenomenon of SIN, and define the dynamic topology model. Based on the system’s discussion of dynamic evolution rules, we propose a weighted local-world dynamic evolution model of SIN including the construction algorithm and implementation process. We achieve the quantitative analysis from four indicators including the node degree, node strength, edge weight, and correlation of strength and degree. Through the univariate control method, we analyze the impact on the network topology features of parameters: local-world M and extra traffic load α. Simulation results show that they have similar topology structure features with the theoretical analysis and real networks, and also verify the validity and feasibility of the proposed model. Finally, we summarize the advantages and disadvantages of the weighted local-world dynamic evolution model of SIN, and look forward to the future work. The research aim of this paper is to provide some methods and techniques to support the construction and management of SIN.

As an important national strategy infrastructure, the Space Information Network (SIN) is a powerful platform for future information support. In this paper, we design and implement a user-centered, dynamic, interactive visualization system (SINDVis), and aim to assist multi-class users to understand, build, develop, maintain, and manage the SIN. We introduce the concept and architecture of SIN, summarize the key technologies of dynamic visualization and visual analysis, and analyze the basic characteristics of three types of users. Combining the content above, we design the architecture of SINDVis from an input module, a core-processing module, an output module, and a user body. We also describe eight basic functions of the entity domain view (GeoView) and topology domain view (TopolView). Meanwhile, we analyze the implementation methods of the GeoView and TopolView, including an improved Force-Directed Algorithm (FDA) layout, Fusion of Animation and Timeline (FAT) visualization, and Panning and Zooming (P&Z) interactions. We analyze the experiment platforms and running environments of the GeoView and TopolView and realize the main contents of both views with a typical SIN. The results also verify the validity and feasibility of the theories and methods proposed. Finally, we discuss and analyze experimental results and the advantages and disadvantages of the SINDVis and look forward to future work. With the development of visualization and visual analysis technology, both application-driven and user-interaction features are gradually highlighted. We introduce the visualization technology into the field of SIN in order to provide new ideas for the basic theory and key technology research of SIN.

Multiplex networks have been widely used to describe the multi-type connections of entities in the real world. However, researches for multiplex networks visualization unilaterally focus on the presentation of topological structure, lacking of specific high-level information presentation for quantitative comparison of interlayer structure. Users cannot participate in the exploration and freely choose the layers (or sub-graphs, regions, etc.) of interest for structural comparison. Contraposing the layer-edge patterns visual analysis tasks of multiplex networks, this paper puts forward a novel solution for exploration and analysis that tightly couples topological structure and high-level patterns. It mainly contains a multi-force directed model to realize the balanced layout of nodes in multi-layer topology, as well as two kinds of high-level patterns of which the visual representations are, respectively, designed by a familiar metaphor—that is, the similar pattern representation based on the area-proportional Venn diagrams and the interaction pattern representation based on the directed arrows. Furthermore, views association is implemented through underlying data sharing and multiple interactions which can be used to gain insights through the creation of selections of interest and produce high-level infographic-style overviews simultaneously. The experiments on real-world data demonstrate the support of the proposed method for layer-edge patterns analysis tasks in multiplex networks and the effectiveness for analyzing the multi-layer structure of multiplex networks.