Patent ID: 11924049
Assignee: ACCEDIAN NETWORKS INC.
Field: Digital communication (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 0:
1. A method for detecting anomalies in one or more time series relating to one or more performance measures for one or more monitored objects in one or more networks comprising:
selecting, by a processor, a discrete window on one of said one or more time series to extract a first motif for a first performance measure of said one or more performance measures for a first monitored object of said one or more monitored objects;
maintaining, by the processor, an abnormal cluster center and a normal cluster center, from a binary clustering of one or more historical time series for said first performance measure for said first monitored object;
classifying, by the processor, said first motif based on a distance between said first motif and said abnormal cluster center and said normal cluster center; and
determining, by the processor, whether an anomaly for said first performance measure for said first monitored object occurred based on said distance and a predetermined decision boundary.