A nonparametric cusum algorithm for timeslot sequences with applications to network surveillance

We adapt the classic cusum change-point detection algorithm for applications to data network monitoring where various and numerous performance and reliability metrics are available to aid with early identification of realized or impending failures. Three significant challenges that must be overcome are: 1) the need for a nonparametric technique so that a wide variety of metrics (including discrete metrics) can be included in the monitoring process, 2) the need to handle time varying distributions for the metrics that reflect natural cycles in work load and traffic patterns, and 3) the need to be computationally efficient with data processing of the massive number of metrics that are available from IT environments.