A Study on Network Traffic Rendering by a Hyper-Object

互联网被如此多的人以各种方式使用，并且有越来越多的因素给互联网通信带来意想不到的困难。无论是管理者还是最终用户都希望了解当前网络中通信趋势的质的变化。定性方面的视觉呈现有助于直观地理解现在网络上发生的复杂现象。我们的研究目的是通过隐喻的方式来抽象网络使用中的特征数据，以直观的方式呈现网络使用情况，首先假设父母希望看到孩子使用互联网的情况，以避免接触有害信息。我们已经提出并实现了Web访问看门狗系统，它工作在一个儿童的PC连接到互联网。看门狗系统通过捕获数据包的方式检测网络访问情况，并从下载的网页文本中抽取单词。通过电子邮件定期向父母报告访问趋势分析的图形表示。在此基础上，提出了一种基于通信流量动态聚类分析的超对象图形化流量绘制方法。超对象具有类似球体的虚拟3D形状，聚类结果映射到该球体上，以引起对网络中复杂现象的直观理解。通过自组织映射，在虚拟球体上动态地形成一个簇，簇是具有相似流量模式的主机的集合。我们使用实际网络流量数据评估了原型实现和可视化实验。

The Internet is used by so many people in various ways, and there are growing factors to bring unexpected difficulty in the Internet communications. Not only administrators but also end-users want to know qualitative changes of the communication tendency in the current network. Visual presentation for the qualitative aspects is helpful to understand the complex phenomena intuitively that is happening on the network now. Our research objective is to give the visual presentation on the network utilization by a metaphor to abstract the characteristic data in the network access.At first, we have supposed a situation such as parents want to see their children's use of the Internet to avoid risks of contact with harmful information. We have proposed and implemented the Web access watchdog system which works on a children's PC connected to the Internet. The watchdog system always checks the Internet access by packet capturing, and samples the words from downloaded text of Web pages. A graphical presentation of the access tendency analysis is periodically reported to the parents via e-mail. We have evaluated the overhead for packet capturing and tendency analysis.Then, we have supposed the Internet traffic monitoring and proposed a hyper-object which is a graphical traffic rendering approach based on a dynamic clustering analysis of communication traffic. The hyper-object has a virtual 3D shape like a sphere on which the clustering results are mapped to cause intuitive understanding of complex phenomena in the network. A cluster, which is a set of hosts with similar traffic patterns, is dynamically formed on the virtual sphere by self-organization mapping. We have evaluated the prototype implementation and the visualization experiments by using actual network traffic data.