A cusum change-point detection algorithm for non-stationary sequences with application to data network surveillance

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• 作者：Veronica Montes De Oca ; Daniel R. Jeske ; Qi Zhang ; Carlos Rendon ; Mazda Marvasti
• 关键词：Network surveillance ; On-line detection ; Screening ; Cusum algorithm
• 刊名：Journal of Systems and Software
• 出版年：2010
• 出版时间：July 2010
• 年：2010
• 卷：83
• 期：7
• 页码：1288-1297
• 全文大小：770 K

文摘

We adapt the classic cusum change-point detection algorithm to handle non-stationary sequences that are typical with network surveillance applications. The proposed algorithm uses a defined timeslot structure to take into account time varying distributions, and uses historical samples of observations within each timeslot to facilitate a nonparametric methodology. Our proposed solution includes an on-line screening feature that fully automates the implementation of the algorithm and eliminates the need for manual oversight up until the point where root cause analysis begins.