基于SVG的动态拓扑可视化系统的设计与实现

发布时间：2018-06-16 22:27

本文选题：动态拓扑 + 动态渲染　；参考：《电子科技大学》2017年硕士论文

【摘要】：计算机的普及以及互联网的高速发展促使信息网络越来越复杂,同时造成了网络拓扑在感知以及分析上的难度。主要体现在数据的复杂性、节点间关系的复杂性、以及节点管控的复杂性上。此外,网络拓扑是一个动态的整体,拓扑的状态、组成拓扑的节点以及节点间的关系都在时刻变化着。这些因素交织在一起,将明显降低对网络拓扑感知以及分析的效率。针对这一问题,提出了一种基于SVG的动态拓扑可视化系统的设计。针对网络拓扑自身动态性、复杂性等特点造成的分析难、维护难、管控难等问题进行了系统地研究以及一些工程性地探索,包括拓扑数据的组织与传输、数据动态化机制的研究、渲染算法以及通信机制的设计与优化等。具体工作内容如下:1.提出了一种动态拓扑可视化方案,将抽象的拓扑连接关系以及节点的信息以界面的形式进行展示,提供多种视图对应拓扑数据多个维度的展示,并依靠后台数据服务器提供一定的交互功能,简化网络拓扑数据分析、管控难度。2.提出了一种基于WebSocket的订阅/分发模式的页面间通信机制,通过页面ID配合后台服务器路由机制实现本机页面间通信以及多机页面通信,用于多维度拓扑态势展示页面的页面间动作同步。3.设计了一种基于SVG的自适应动画渲染优化算法,通过动画-回调函数归并优化提高了渲染性能。较原生渲染算法提高了渲染效率与稳定性,支持数百个动画同时进行渲染,用于支持拓扑节点间的数据交互的可视化。4.设计了一种稳定可靠的拓扑数据动态更新机制,能够有效识别森林中的公共节点并进行融合。对于失效节点能够动态的进行状态下线并解除与拓扑之间的通联关系。对于节点间的指派关系、以及操作能够动态的生成关系连线以及动画。5.设计了一种新的图数据组织结构,解决了图数据环路造成的Json数据解析无限递归问题,同时精简了数据存储复杂度提高了数据传输效率。经测试,动态拓扑态势系统能够动态捕捉网络拓扑中节点、连接关系、指派关系等一些要素信息,具备实时性、高准确性、分析维度全面、易操作等特点。解决了对于网络拓扑数据抽象化程度高、关系复杂难以分析与管控等难点。大大提高了拓扑态势感知与分析效率。
[Abstract]:The popularity of computers and the rapid development of the Internet make the information network more and more complex, and at the same time, it is difficult to perceive and analyze the network topology. It is mainly reflected in the complexity of data, the complexity of the relationship between nodes, and the complexity of node control. In addition, the network topology is a dynamic whole, the state of the topology, the nodes that make up the topology and the relationship between the nodes are changing at all times. These factors will reduce the efficiency of network topology perception and analysis. To solve this problem, a dynamic topology visualization system based on SVG is proposed. Aiming at the difficulties of analysis, maintenance and control caused by the dynamic and complex characteristics of network topology, this paper makes a systematic study and some engineering exploration, including the organization and transmission of topological data. The research of data dynamic mechanism, the design and optimization of rendering algorithm and communication mechanism. The details of the work are as follows: 1. In this paper, a dynamic topology visualization scheme is proposed, in which abstract topology connection and node information are displayed in the form of interface. And rely on backstage data server to provide certain interactive function, simplify network topology data analysis, control difficulty. 2. 2. In this paper, a WebSocket-based subscription / distribution mode communication mechanism between pages is proposed. The communication between local pages and multi-machine pages is realized by using page ID and background server routing mechanism. Interpage action synchronization. 3. 3 for multi-dimensional topology situation display pages. An adaptive animation rendering optimization algorithm based on SVG is designed, and the rendering performance is improved by the combination optimization of animation-callback function. Compared with the native rendering algorithm, it improves the efficiency and stability of rendering, supports hundreds of animations to render simultaneously, and is used to support the visualization of data interaction between topology nodes. A stable and reliable dynamic updating mechanism of topological data is designed, which can effectively identify and fuse the common nodes in the forest. Failure nodes can be dynamically disconnected from the state and unconnected to the topology. For the assignment relationship between nodes, as well as the operation can dynamically generate the relationship line and animation. 5. 5. A new structure of graph data organization is designed, which solves the problem of infinite recursion of Json data analysis caused by graph data loop, and simplifies the complexity of data storage and improves the efficiency of data transmission. The test results show that the dynamic topological situation system can dynamically capture the information of nodes, connections and assignment relationships in network topology, which has the characteristics of real-time, high accuracy, comprehensive analysis dimension and easy to operate. It solves the difficulties such as high abstract degree of network topology data, complex relationship, difficult to analyze and control. The efficiency of topological situational awareness and analysis is greatly improved.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.0

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