The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 07, 2022

Filed:

Jul. 23, 2020
Applicant:

Ciena Corporation, Hanover, MD (US);

Inventors:

David Côté, Gatineau, CA;

Petar Djukic, Ottawa, CA;

Thomas Triplet, Manotick, CA;

Todd Morris, Stittsville, CA;

Paul Gosse, Ottawa, CA;

Dana Dennis, Kingston, CA;

Emil Janulewicz, Ottawa, CA;

Patrick Premont, Ottawa, CA;

Assignee:

Ciena Corporation, Hanover, MD (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04J 3/14 (2006.01); H04L 41/0631 (2022.01); H04L 41/12 (2022.01); G06N 20/00 (2019.01); H04L 41/16 (2022.01); G06N 5/04 (2006.01); H04J 3/16 (2006.01); H04B 10/079 (2013.01); G06K 9/62 (2022.01);
U.S. Cl.
CPC ...
H04L 41/065 (2013.01); G06K 9/6256 (2013.01); G06N 5/045 (2013.01); G06N 20/00 (2019.01); H04B 10/07953 (2013.01); H04J 3/1652 (2013.01); H04L 41/12 (2013.01); H04L 41/16 (2013.01);
Abstract

Systems and methods for detecting patterns in data from a time-series are provided. According to some implementations, the systems and methods may use network topology information combined with object recognition techniques to detect patterns. One embodiment of a method includes the steps of obtaining information defining a topology of a multi-layer network having a plurality of Network Elements (NEs) and a plurality of links interconnecting the NEs and receiving Performance Monitoring (PM) metrics and one or more alarms from the multi-layer network. Based on the information defining the topology, the PM metrics, and the one or more alarms, the method also includes the step of utilizing a Machine Learning (ML) process to identify a problematic component from the plurality of NEs and links and to identify a root cause associated with the problematic component.


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