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Active measurements on network paths provide end-to-end network health status in terms of metrics such as bandwidth, delay, jitter and loss. Hence, they are increasingly being used for various network control and management functions on the Internet. For purposes of network health anomaly detection and forecasting involved in these functions, it is important to accurately model the time-series process of active measurements. In this paper, the authors describe the time-series analysis of two typical active measurement data sets collected over several months: routine, and event-laden.
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