Incremental steady-state layout method for time-varying network data

Abstract

The invention discloses an incremental steady-state layout method for time-varying network data. The incremental steady-state layout method comprises the following steps: loading network structure data; preprocessing the data; generating an initial static graph by adopting a multi-level method; initializing node positions for newly added nodes; adjusting the length of the edge for the newly-addededge; calculating the level attribute of the node; partitioning the nodes, calculating the repulsive force in the form of pseudo nodes, and simplifying the layout updating process of the force guidingalgorithm. According to the invention, a stable layout method for time-varying network data is designed as a starting point; a force guide graph is used as a basic visual presentation mode; network structure characteristics such as'node level 'are introduced, it is guaranteed that focus of interest of a user does not change suddenly in the large-range change process of the network topology structure, the stability and continuity of the cognitive process of the user are kept, the user is helped to understand the topology structure of a complex network more effectively, and the understanding difficulty of the time-varying network topology structure is reduced.

Description

technical field [0001] The present invention relates to a network data layout method, in particular to an incremental steady-state layout method for time-varying network data. Background technique [0002] Network topology discovery and display is the primary task of modern network management. With the help of network topology results, you can understand the current network operating status, judge network congestion / locate network bottlenecks, find network faults and analyze the causes and locations of occurrences, so as to realize the entire network. Timely and effective monitoring and control of the operating status. Visualization is a science and technology that assists users to analyze and reason large-scale and complex data sets through an interactive visual interface. Comprehension and awareness of information. Network topology visualization presents the connection relationship of network nodes in graphic images composed of points and lines, which can clearly and int...

AI Technical Summary

Problems solved by technology

However, network time-varying data may undergo drastic changes in network scale and network structure during the spatiotemporal evolution process. The types and numbers of network nodes contained in network time-varying data are constantly changing with time, and the connection relationship between network nodes is also constantly emerging. The network topology is constantly changing in the process of nodes appearing and disappearing. Large-scale network layout updates will cause serious cognitive confusion for users and increase the difficulty of understanding the time-varying network topology.

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