Patents by Inventor Fernando Maisonett

Fernando Maisonett 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).

  • Machine Learning-Based Multitenant Server Application Dependency Mapping System
    Publication number: 20240348599
    Abstract: A multitenant server application dependency mapping system maps data flows through multitenant infrastructure components through the use of a machine learning model framework that continually learns data flow patterns across the enterprise network and predicts the state of any given server. The multitenant server application dependency mapping system treats the network architecture as a whole and collects data accordingly, and uses that data to compute state probabilities conditioned upon both a point in time (and the observed prior states retrieved from the historical telemetry data. This provides a way to predict the likelihood of observing a tenant state being occupied, while also accounting for variations among the activity levels of various application.
    Type: Application
    Filed: June 27, 2024
    Publication date: October 17, 2024
    Applicant: Bank of America Corporation
    Inventors: Conor Mitchell Liam Nodzak, Fernando Maisonett, Shreyas Srinivas, Brian Busch
  • Machine learning-based multitenant server application dependency mapping system
    Patent number: 12052146
    Abstract: A multitenant server application dependency mapping system maps data flows through multitenant infrastructure components through the use of a machine learning model framework that continually learns data flow patterns across the enterprise network and predicts the state of any given server. The multitenant server application dependency mapping system treats the network architecture as a whole and collects data accordingly, and uses that data to compute state probabilities conditioned upon both a point in time (and the observed prior states retrieved from the historical telemetry data. This provides a way to predict the likelihood of observing a tenant state being occupied, while also accounting for variations among the activity levels of various application.
    Type: Grant
    Filed: December 5, 2022
    Date of Patent: July 30, 2024
    Assignee: Bank of America Corporation
    Inventors: Conor Mitchell Liam Nodzak, Fernando Maisonett, Shreyas Srinivas, Brian Busch, Kyle Scott Sorensen
  • Machine Learning-Based Multitenant Server Application Dependency Mapping System
    Publication number: 20240187311
    Abstract: A multitenant server application dependency mapping system maps data flows through multitenant infrastructure components through the use of a machine learning model framework that continually learns data flow patterns across the enterprise network and predicts the state of any given server. The multitenant server application dependency mapping system treats the network architecture as a whole and collects data accordingly, and uses that data to compute state probabilities conditioned upon both a point in time (and the observed prior states retrieved from the historical telemetry data. This provides a way to predict the likelihood of observing a tenant state being occupied, while also accounting for variations among the activity levels of various application.
    Type: Application
    Filed: December 5, 2022
    Publication date: June 6, 2024
    Inventors: Conor Mitchell Liam Nodzak, Fernando Maisonett, Shreyas Srinivas, Brian Busch, Kyle Scott Sorensen