Patents by Inventor Rahul Kumar K Sevakula

Rahul Kumar K Sevakula 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 for failure event identification and prediction
    Patent number: 11222287
    Abstract: Techniques for failure prediction are provided. A plurality of event indications is received, where each respective event indication corresponds to a respective failure in a computing system. A plurality of machine learning (ML) models is trained based on combinations of event indications in the plurality of event indications, and the ML models are evaluated to generate a respective quality score for each respective ML model. An ensemble of ML models is defined from the plurality of ML models, based on identifying ML models of the plurality of ML models with corresponding quality scores exceeding a predefined threshold. Current data logs from the computing system are processed using the ensemble of ML models, and upon determining that any ML model of the ensemble of ML models predicted a failure based on the current data logs, an alert is generated.
    Type: Grant
    Filed: July 25, 2019
    Date of Patent: January 11, 2022
    Assignee: International Business Machines Corporation
    Inventors: Rahul Kumar K Sevakula, Parag Sanjay Mhatre
  • MACHINE LEARNING FOR FAILURE EVENT IDENTIFICATION & PREDICTION
    Publication number: 20210027205
    Abstract: Techniques for failure prediction are provided. A plurality of event indications is received, where each respective event indication corresponds to a respective failure in a computing system. A plurality of machine learning (ML) models is trained based on combinations of event indications in the plurality of event indications, and the ML models are evaluated to generate a respective quality score for each respective ML model. An ensemble of ML models is defined from the plurality of ML models, based on identifying ML models of the plurality of ML models with corresponding quality scores exceeding a predefined threshold. Current data logs from the computing system are processed using the ensemble of ML models, and upon determining that any ML model of the ensemble of ML models predicted a failure based on the current data logs, an alert is generated.
    Type: Application
    Filed: July 25, 2019
    Publication date: January 28, 2021
    Inventors: Rahul Kumar K Sevakula, Parag Sanjay Mhatre