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System and method of predicting future behavior of a battery of end-to-end probes to anticipate and prevent computer network performance degradation
System and method of predicting future behavior of a battery of end-to-end probes to anticipate and prevent computer network performance degradation
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机译：预测端对端探针电池的未来行为以预测和防止计算机网络性能下降的系统和方法
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摘要
A diagnostic system in which, at every point in time, a forecast is made of the future response times of each EPP (End-to-end Probe Platform) probe in a battery of probes. Thresholds are established in terms of the distribution of future EPP values. The theory of Generalized Additive Models is used to build a predictive model based on a combination of a) data normally generated by network nodes, b) results of a battery of probes and c) profile curves reflecting expected response times (i.e. based on recent history) corresponding to this battery for various times of day, days of week, month of year, etc. The model is pre-computed, and does not have to be dynamically adjusted. The model produces, at regular intervals, forecasts for outcomes of various EPP probes for various horizons of interest; also, it produces thresholds for the respective forecasts based on a number of factors, including acceptable rate of false alarms, forecast variance and EPP values that are expected based on the recorded history. The system is capable of maintaining a pre-specified low rate of false alarms that could otherwise cause a substantial disturbance in network operation.
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机译：一种诊断系统，其中，每个时间点都会预测每个EPP的未来响应时间（ E 端到端 P robe P latform）探头。阈值是根据未来EPP值的分布确定的。广义可加模型的理论用于基于以下组合来构建预测模型：a）网络节点通常生成的数据，b）一组电池的结果，以及c）反映预期响应时间的轮廓曲线（即基于最近的历史记录） ）对应于该电池在一天中的不同时间，一周中的某天，一年中的某个月等。该模型是预先计算的，无需动态调整。该模型会定期生成针对各种关注水平的各种EPP探测结果的预测;此外，它还基于许多因素为各个预测生成阈值，包括可接受的错误警报率，预测方差和根据记录的历史预期的EPP值。该系统能够维持预先规定的较低的误报率，否则可能导致网络运行受到严重干扰。
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