Patents by Inventor Dinko Papak

Dinko Papak 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).

  • Patent number: 11036715
    Abstract: Methods, systems, apparatuses, and computer program products are described herein that enable detecting anomalies in time series. An anomaly detection technique is selected from a plurality of detection techniques, and is applied to a first time-series data set (having a first set of dimensions). In response to detecting an anomaly in the time-series data set, the anomaly detection technique is applied to a second time-series data set that is a subset of the first time-series data set. The first time-series data set includes the first set of dimensions plus one or more additional dimensions.
    Type: Grant
    Filed: January 29, 2018
    Date of Patent: June 15, 2021
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Varun Jain, Dmitri A. Klementiev, Igor Sakhnov, Dinko Papak, LeninaDevi Thangavel, Michail Zervos, Dhruv Gakkhar, Kateryna Boikovska
  • Patent number: 10467126
    Abstract: A system determines a topology of a distributed system and determines, based on the topology, one or more injection points in the distributed system to inject failure scenarios. Each failure scenario including one or more faults and parameters for each of the faults. The system prioritizes the failure scenarios and injects a failure scenario from the prioritized failure scenarios into the distributed system via the one or more injection points. The system determines whether the injected failure scenario causes a response of the distributed system to fall below a predetermined level. The system determines resiliency of the distributed system to one or more faults in the injected failure scenario based on whether the injected failure scenario causes the response of the distributed system to fall below the predetermined level.
    Type: Grant
    Filed: March 31, 2017
    Date of Patent: November 5, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Dinko Papak, Michail Zervos, Dmitri A. Klementiev, Dhruv Gakkhar, Varun Jain, LeninaDevi Thangavel, Igor Sakhnov
  • Patent number: 10387231
    Abstract: A method and system for assessing resiliency of a system is provided. A fault injection system may, for each of a plurality of dimensions of a fault profile, access an indication of possible values for the dimension, which may be specified by a user. The fault injection system may, for each of a plurality of fault profiles, automatically create the fault profile by, for each of the plurality of dimensions, selecting by the computing system a possible value for that dimension. For at least some of the fault profiles, the fault injection system injects a fault based on the fault profile into the system and determines whether a failure was detected while the fault was injected.
    Type: Grant
    Filed: September 22, 2016
    Date of Patent: August 20, 2019
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Dinko Papak, LeninaDevi Thangavel, Richard Gregory Endean, Jr., Dmitri A. Klementiev, Dhruv Gakkhar, Varun Jain, Michail Zervos
  • Publication number: 20190236177
    Abstract: Methods, systems, apparatuses, and computer program products are described herein that enable detecting anomalies in time series. An anomaly detection technique is selected from a plurality of detection techniques, and is applied to a first time-series data set (having a first set of dimensions). In response to detecting an anomaly in the time-series data set, the anomaly detection technique is applied to a second time-series data set that is a subset of the first time-series data set. The first time-series data set includes the first set of dimensions plus one or more additional dimensions.
    Type: Application
    Filed: January 29, 2018
    Publication date: August 1, 2019
    Inventors: Varun Jain, Dmitri A. Klementiev, Igor Sakhnov, Dinko Papak, LeninaDevi Thangavel, Michail Zervos, Dhruv Gakkhar, Kateryna Boikovska
  • Publication number: 20180285239
    Abstract: A system determines a topology of a distributed system and determines, based on the topology, one or more injection points in the distributed system to inject failure scenarios. Each failure scenario including one or more faults and parameters for each of the faults. The system prioritizes the failure scenarios and injects a failure scenario from the prioritized failure scenarios into the distributed system via the one or more injection points. The system determines whether the injected failure scenario causes a response of the distributed system to fall below a predetermined level. The system determines resiliency of the distributed system to one or more faults in the injected failure scenario based on whether the injected failure scenario causes the response of the distributed system to fall below the predetermined level.
    Type: Application
    Filed: March 31, 2017
    Publication date: October 4, 2018
    Inventors: Dinko PAPAK, Michail ZERVOS, Dmitri A. KLEMENTIEV, Dhruv GAKKHAR, Varun JAIN, LeninaDevi THANGAVEL, Igor SAKHNOV
  • Publication number: 20180060202
    Abstract: A method and system for assessing resiliency of a system is provided. A fault injection system may, for each of a plurality of dimensions of a fault profile, access an indication of possible values for the dimension, which may be specified by a user. The fault injection system may, for each of a plurality of fault profiles, automatically create the fault profile by, for each of the plurality of dimensions, selecting by the computing system a possible value for that dimension. For at least some of the fault profiles, the fault injection system injects a fault based on the fault profile into the system and determines whether a failure was detected while the fault was injected.
    Type: Application
    Filed: September 22, 2016
    Publication date: March 1, 2018
    Inventors: Dinko Papak, LeninaDevi Thangavel, Richard Gregory Endean, JR., Dmitri A. Klementiev, Dhruv Gakkhar, Varun Jain, Michail Zervos