An Internet user could predict the future status based on the link bandwidth and the local traffic, and then control his own network behavior.
用户根据探测的链路带宽和本地网络的业务状态，对未来状态进行预测，并主动控制自己的网络行为。
CAIDA collects, monitors, analyzes, and visualizes several forms of Internet traffic data concerning network topology, workload characterization, performance, routing, and multicast behavior.
CAIDA收集、监控、分析和可视化以下几种互联网流量数据：关于网络拓扑、工作量特性、性能、路由和多播行为。
Based on statistics character of traffic in a large-scale network, the steady metrics that can estimated network behavior are found and a sampling measurement model is presented in this paper.
基于大规模网络流量的统计特征，寻找能够评价网络行为的稳定测度，并建立抽样测量模型。
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