Patents by Inventor Guruprasad PV

Guruprasad PV 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: 11314542
    Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. A prescriptive engine layer may generate a compute sizing correction trajectory detailing adjustments to sizing for the computing resources. Based on the compute sizing correction trajectory, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.
    Type: Grant
    Filed: July 20, 2020
    Date of Patent: April 26, 2022
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad PV, Michael S. Eisenstein, Vijay Desai
  • Patent number: 11216202
    Abstract: A system includes a multi-layer block storage volume optimization (BSO) stack to generate a BSO token containing prescriptions to optimize block storage volume. The system may receive account information of storage accounts associated with block storage volumes; obtain respective storage regions and respective data redundancy types of the first storage account and the second storage account from the first account information; and generate the BSO token to include instructions to merge the storage accounts according to the respective storage regions and the respective data redundancy types.
    Type: Grant
    Filed: August 8, 2020
    Date of Patent: January 4, 2022
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Guruprasad Pv
  • Publication number: 20210405903
    Abstract: A system includes a multi-layer block storage volume optimization (BSO) stack to generate a BSO token containing prescriptions to optimize block storage volume. The system may receive account information of storage accounts associated with block storage volumes; obtain respective storage regions and respective data redundancy types of the first storage account and the second storage account from the first account information; and generate the BSO token to include instructions to merge the storage accounts according to the respective storage regions and the respective data redundancy types.
    Type: Application
    Filed: August 8, 2020
    Publication date: December 30, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad Pv
  • Patent number: 11210197
    Abstract: A multi-layer tier requisition stack may generate prescriptive tier requisition tokens for controlling requisition of database-compute resources at database-compute tiers. The input layer of the tier requisition stack may obtain historical data and database-compute tolerance data. The coefficient layer may be used to determine activity coefficients for each data type within the historical data. The activity coefficients may then be combined to determine an overall activity factor. The tolerance layer may be used to select an initial database-compute tier based on the activity factor. The tolerance layer may then increase from the initial database compute tier to an adjusted database-compute tier while accommodating tolerances within the database-compute tolerance data. The requisition layer may generate a tier requisition token based on the adjusted database-compute tier and/or finalization directives obtained at the requisition layer.
    Type: Grant
    Filed: June 10, 2020
    Date of Patent: December 28, 2021
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV
  • Publication number: 20210334282
    Abstract: A system includes a multi-layer throughput optimization (TPO) stack to generate a token containing prescriptions for rightsizing database service throughput.
    Type: Application
    Filed: June 9, 2020
    Publication date: October 28, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV, Samba Sivachari Rage
  • Publication number: 20210334191
    Abstract: A multi-layer tier requisition stack may generate prescriptive tier requisition tokens for controlling requisition of database-compute resources at database-compute tiers. The input layer of the tier requisition stack may obtain historical data and database-compute tolerance data. The coefficient layer may be used to determine activity coefficients for each data type within the historical data. The activity coefficients may then be combined to determine an overall activity factor. The tolerance layer may be used to select an initial database-compute tier based on the activity factor. The tolerance layer may then increase from the initial database compute tier to an adjusted database-compute tier while accommodating tolerances within the database-compute tolerance data. The requisition layer may generate a tier requisition token based on the adjusted database-compute tier and/or finalization directives obtained at the requisition layer.
    Type: Application
    Filed: June 10, 2020
    Publication date: October 28, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV
  • Publication number: 20210256066
    Abstract: A multi-layer consumption unit estimation (CUE) stack may generate a consumption preview for prescribing cloud computing resource utilization. An input layer of the CUE stack may obtain computing resource utilization tracking data, consumption metric data, application execution tracking data, and computing resource reservation data for a set of computing resources. A configuration layer of the CUE stack may determine a CUE interval and determine consumption metric modifiers for a selected identity associated with the set of computing resources. A CUE engine layer may generate a consumption preview by advancing a dynamic consumption credit input/output flow analysis and executing a direct utilization consumption determination.
    Type: Application
    Filed: February 19, 2020
    Publication date: August 19, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV, Manish Sharma Kolachalam
  • Patent number: 10871917
    Abstract: A multi-layer rate sizing stack may generate prescriptive operation-rate tokens for controlling sizing adjustments for operation-rates. The input layer of the rate sizing stack may generate operation pattern data based on operation-rate data received via network connection. A prescriptive engine layer may determine a prescriptive allowed operation-rate based on the operation pattern data. Based on the prescriptive allowed operation-rate, the prescriptive engine layer may generate the operation-rate tokens that that may be used to control rate sizing adjustments prescriptively.
    Type: Grant
    Filed: February 26, 2019
    Date of Patent: December 22, 2020
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv, Kishore Kumar Gajula
  • Publication number: 20200348961
    Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. A prescriptive engine layer may generate a compute sizing correction trajectory detailing adjustments to sizing for the computing resources. Based on the compute sizing correction trajectory, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.
    Type: Application
    Filed: July 20, 2020
    Publication date: November 5, 2020
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad PV, Michael S. Eisenstein, Vijay Desai
  • Patent number: 10764370
    Abstract: A cloud migration tool manages and monitors a cloud migration project that migrates data from a legacy environment to a target data center environment. The cloud migration tool includes an analytics engine that applies data regression models to generate a delay risk prediction for activities that are scheduled during the cloud migration project.
    Type: Grant
    Filed: April 30, 2018
    Date of Patent: September 1, 2020
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv
  • Publication number: 20200272355
    Abstract: A multi-layer rate sizing stack may generate prescriptive operation-rate tokens for controlling sizing adjustments for operation-rates. The input layer of the rate sizing stack may generate operation pattern data based on operation-rate data received via network connection. A prescriptive engine layer may determine a prescriptive allowed operation-rate based on the operation pattern data. Based on the prescriptive allowed operation-rate, the prescriptive engine layer may generate the operation-rate tokens that that may be used to control rate sizing adjustments prescriptively.
    Type: Application
    Filed: February 26, 2019
    Publication date: August 27, 2020
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad PV, Kishore Kumar Gajula
  • Patent number: 10742567
    Abstract: A multi-layer storage class placement stack may generate a token containing storage class placement prescriptions for controlling the placement of stored items within a selection of classes for storage. An input layer of the storage class placement stack may generate time-collated activity data based on historical access data, volume metric data, and/or tagging data. The time-collated activity data may include data groupings using timestamps or other timing indicators. A transformation layer may further process the time-collated activity data to generate defined-period summation data that provides summary detail for defined durations across a period of analysis. The defined-period summation data may be used by a prescriptive engine layer to generate prescriptions for placement of individual stored items by associating the prescriptions with storage identifiers for the individual items.
    Type: Grant
    Filed: December 13, 2018
    Date of Patent: August 11, 2020
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv, Manish Sharma Kolachalam
  • Patent number: 10719344
    Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. A prescriptive engine layer may generate a compute sizing correction trajectory detailing adjustments to sizing for the computing resources. Based on the compute sizing correction trajectory, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.
    Type: Grant
    Filed: March 15, 2018
    Date of Patent: July 21, 2020
    Assignee: Acceture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv, Michael S. Eisenstein, Vijay Desai
  • Patent number: 10712958
    Abstract: A system for elastic volume type selection and optimization is provided. The system may detect that a block storage volume was provisioned by a public cloud computing platform based on a first volume type identifier of a first volume type. The system may determine, based on a normalization model, a baseline operation rate and a baseline throughput rate for the provisioned block storage volume. The system may determine, based on a selected transition mode and historical performance measurements, a simulated operation rate and a simulated throughput rate. The system may communicate, in response to the simulated throughput being greater than the baseline throughput rate or the simulated operation rate being greater than the baseline operation rate, a provisioning instruction to re-provision the provisioned block storage volume on the cloud computing platform.
    Type: Grant
    Filed: October 8, 2018
    Date of Patent: July 14, 2020
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv
  • Publication number: 20200195571
    Abstract: A multi-layer storage class placement stack may generate a token containing storage class placement prescriptions for controlling the placement of stored items within a selection of classes for storage. An input layer of the storage class placement stack may generate time-collated activity data based on historical access data, volume metric data, and/or tagging data. The time-collated activity data may include data groupings using timestamps or other timing indicators. A transformation layer may further process the time-collated activity data to generate defined-period summation data that provides summary detail for defined durations across a period of analysis. The defined-period summation data may be used by a prescriptive engine layer to generate prescriptions for placement of individual stored items by associating the prescriptions with storage identifiers for the individual items.
    Type: Application
    Filed: December 13, 2018
    Publication date: June 18, 2020
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv, Manish Sharma Kolachalam
  • Publication number: 20200034057
    Abstract: A system for elastic volume type selection and optimization is provided. The system may detect that a block storage volume was provisioned by a public cloud computing platform based on a first volume type identifier of a first volume type. The system may determine, based on a normalization model, a baseline operation rate and a baseline throughput rate for the provisioned block storage volume. The system may determine, based on a selected transition mode and historical performance measurements, a simulated operation rate and a simulated throughput rate. The system may communicate, in response to the simulated throughput being greater than the baseline throughput rate or the simulated operation rate being greater than the baseline operation rate, a provisioning instruction to re-provision the provisioned block storage volume on the cloud computing platform.
    Type: Application
    Filed: October 8, 2018
    Publication date: January 30, 2020
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv
  • Patent number: 10523519
    Abstract: A multi-layer analytics service stack may generate forecasted utilization data. An input layer of the analytics service stack may receive input and designate cloud computing utilization data for analysis. A transformation layer of the analytics service stack may perform format transformations on the cloud computing utilization data, and the data may be prepared for analysis at a data treatment layer of the cloud computing utilization data. The treated and transformed cloud computing utilization data may be analyzed using multiple analytics models by a multi-forecasting layer of analytics service stack to generate the forecasted utilization data.
    Type: Grant
    Filed: June 29, 2017
    Date of Patent: December 31, 2019
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad Pv
  • Patent number: 10459757
    Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. The input layer may receive one or more resource configurations that may be applied to implement the sizing correction. A prescriptive engine layer may generate a compute sizing correction trajectory indicative of a sizing adjustment to a computing resource. The compute sizing correction trajectory may account of historic processor, network, and memory utilization. Based on the compute sizing correction trajectory and a selected resource configuration, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.
    Type: Grant
    Filed: May 13, 2019
    Date of Patent: October 29, 2019
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Guruprasad Pv, Arun Purushothaman
  • Publication number: 20190205150
    Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. A prescriptive engine layer may generate a compute sizing correction trajectory detailing adjustments to sizing for the computing resources. Based on the compute sizing correction trajectory, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.
    Type: Application
    Filed: March 15, 2018
    Publication date: July 4, 2019
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad PV, Michael S. Eisenstein, Vijay Desai
  • Publication number: 20190182323
    Abstract: A cloud migration tool manages and monitors a cloud migration project that migrates data from a legacy environment to a target data center environment. The cloud migration tool includes an analytics engine that applies data regression models to generate a delay risk prediction for activities that are scheduled during the cloud migration project.
    Type: Application
    Filed: April 30, 2018
    Publication date: June 13, 2019
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Guruprasad Pv