Patents by Inventor Mitchell Gregory SPRYN

Mitchell Gregory SPRYN 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).

  • Framework for providing recommendations for migration of a database to a cloud computing system
    Patent number: 11481616
    Abstract: To obtain one or more recommendations for the migration of a database to a cloud computing system, information about performance of the database operating under a workload may be obtained. A first machine learning model (e.g., a neural network-based autoencoder) may be used to generate a compressed representation of characteristics of the database operating under the workload. The compressed representation may then be provided as input to a second machine learning model (e.g., a neural network-based classifier), which outputs a recommendation regarding a characteristic (e.g., size, configuration, level of service) of the cloud database to which the database should be migrated. This type of recommendation may be made prior to migration, thereby making it easier to properly estimate the cost of running the cloud database and plan the migration accordingly.
    Type: Grant
    Filed: November 21, 2018
    Date of Patent: October 25, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Mitchell Gregory Spryn, Intaik Park, Felipe Vieira Frujeri, Vijay Govind Panjeti, Ashok Sai Madala, Ajay Kumar Karanam
  • FRAMEWORK FOR PROVIDING RECOMMENDATIONS FOR MIGRATION OF A DATABASE TO A CLOUD COMPUTING SYSTEM
    Publication number: 20200005136
    Abstract: To obtain one or more recommendations for the migration of a database to a cloud computing system, information about performance of the database operating under a workload may be obtained. A first machine learning model (e.g., a neural network-based autoencoder) may be used to generate a compressed representation of characteristics of the database operating under the workload. The compressed representation may then be provided as input to a second machine learning model (e.g., a neural network-based classifier), which outputs a recommendation regarding a characteristic (e.g., size, configuration, level of service) of the cloud database to which the database should be migrated. This type of recommendation may be made prior to migration, thereby making it easier to properly estimate the cost of running the cloud database and plan the migration accordingly.
    Type: Application
    Filed: November 21, 2018
    Publication date: January 2, 2020
    Inventors: Mitchell Gregory SPRYN, Intaik PARK, Felipe VIEIRA FRUJERI, Vijay Govind PANJETI, Ashok Sai MADALA, Ajay Kumar KARANAM