计算机网络流量的统计建模与预测
Network-wide Statistical Modeling and Prediction of Computer Traffic
摘要：
为了保持一致的服务质量，计算机网络工程师面临的任务是监控组成网络的各个链路上的流量波动。然而，由于资源限制和准入有限，不可能直接衡量所有环节。从一个物理上可解释的概率模型的网络范围内的流量，我们演示了如何昂贵地获得一组测量可用于开发一个特定于网络的模型，整个网络的流量。然后，该模型可以与容易获得的测量结果结合使用，以提供比仅使用廉价测量结果更准确的预测。我们表明，该模型，一旦学习可以用于同一网络的许多不同时期的流量。最后，我们展示了一个应用程序的预测技术，以创建相关的控制图，检测和隔离网络流量的变化。
英文摘要：
In order to maintain consistent quality of service, computer network engineers face the task of monitoring the traffic fluctuations on the individual links making up the network. However, due to resource constraints and limited access, it is not possible to directly measure all the links. Starting with a physically interpretable probabilistic model of network-wide traffic, we demonstrate how an expensively obtained set of measurements may be used to develop a network-specific model of the traffic across the network. This model may then be used in conjunction with easily obtainable measurements to provide more accurate prediction than is possible with only the inexpensive measurements. We show that the model, once learned may be used for the same network for many different periods of traffic. Finally, we show an application of the prediction technique to create relevant control charts for detection and isolation of shifts in network traffic.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
