Patents by Inventor Patrick Premont

Patrick Premont has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Identifying and locating a root cause of issues in a network having a known topology
    Patent number: 11356320
    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.
    Type: Grant
    Filed: July 23, 2020
    Date of Patent: June 7, 2022
    Assignee: Ciena Corporation
    Inventors: David Côté, Petar Djukic, Thomas Triplet, Todd Morris, Paul Gosse, Dana Dennis, Emil Janulewicz, Patrick Premont
  • Identifying and locating a root cause of issues in a network having a known topology
    Publication number: 20210028973
    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.
    Type: Application
    Filed: July 23, 2020
    Publication date: January 28, 2021
    Inventors: David Côté, Petar Djukic, Thomas Triplet, Todd Morris, Paul Gosse, Dana Dennis, Emil Janulewicz, Patrick Premont