Online non-parametric changepoint detection with application to monitoring operational performance of network devices
提出一种名为NUNC的非参数在线变点检测算法，包含局部和全局两种变体，能有效监测网络设备运行性能的变化，并给出控制虚警率的理论阈值选择方法。
Motivated by a telecommunications application where there are few computational constraints, a novel nonparametric algorithm, NUNC, is introduced to perform an online detection for changes in the distribution of data. Two variants are considered: the first, NUNC Local, detects changes within a sliding window. Conversely, NUNC Global, compares the current window of data to all of the historic information seen so far and makes use of an efficient update step so that this historic information does not need to be stored. To explore the properties of both algorithms, both real and simulated datasets are analysed. Furthermore, a theoretical result for the choice of test threshold to control the false alarm rate is presented, a result that could be applied in other binary segmentation change detection settings.