Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

Large Scale Network Topology Visualization System Based on Three.JS

Authors
Yuxiao Wang, Yuanzhang Li, Yu'an Tan, Quanxin Zhang, Jun Zheng
Corresponding Author
Yuxiao Wang
Available Online January 2016.
DOI
10.2991/icaita-16.2016.39How to use a DOI?
Keywords
web 3D; three.JS; network topology; visualization; node.JS
Abstract

with the rapid development of visualization, network visualization has become an important branch, which is applied in many aspects of life such as business, education and virtual community. But existed network visualization systems are based on small volume and static effect. Along with the incessant expansion of modern internet scale, traditional tools’ practicality decrease. Showing huge information of network clearly and effectively will be of great signification. In our paper, large-scale network topology visualization system is finished by using Web 3D technique—Three.JS in process of building and analysis, which can display topology clearly. As middleware, Node.JS can transfer communication data forward or backward instantaneously, which can solve the problem of dynamic and real-time 3D effects. Node-Webkit framework helps realize its cross-platform feature. This solution can run smoothly and clearly under the 103 order of magnitudes network topology. It makes large scale network visualization more direct and convenient.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
978-94-6252-162-9
ISSN
1951-6851
DOI
10.2991/icaita-16.2016.39How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuxiao Wang
AU  - Yuanzhang Li
AU  - Yu'an Tan
AU  - Quanxin Zhang
AU  - Jun Zheng
PY  - 2016/01
DA  - 2016/01
TI  - Large Scale Network Topology Visualization System Based on Three.JS
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 152
EP  - 155
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.39
DO  - 10.2991/icaita-16.2016.39
ID  - Wang2016/01
ER  -