Patents by Inventor Kumar Srinivasan

Kumar Srinivasan 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: 11462220
    Abstract: A device may receive user personalized data and user activity data identifying tasks and actions performed by a user, and may perform natural language processing on the user personalized data and the user activity data to generate processed textual data. The device may train machine learning models based on the processed textual data to generate trained machine learning models, and may receive, from a client device, a command identifying a particular task to be performed. The device may process the command and the user activity data, with the trained machine learning models, to determine whether a particular action in the user activity data correlates with the particular task. The device may perform actions when the particular action correlates with the particular task.
    Type: Grant
    Filed: March 4, 2020
    Date of Patent: October 4, 2022
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Sumanta Kayal, Moushom Borah, Abhijit Ghosh
  • Publication number: 20220300471
    Abstract: A multi-layer database sizing stack may generate prescriptive tier requisition tokens for controlling requisition of database-compute resources at database-compute tiers. The input layer of the database sizing stack may obtain historical data. The threading layer may be used to flag occurrences of single threading application execution. The change layer may be used to determine potential for a step based on compute utilization type data and assert flags indicating the potential. The step layer may determine if potential steps may be taken based on operation-rate type data and flush type data. The requisition layer may generate a tier requisition token based on the provisional requisition tokens generated at other layers and/or finalization directives obtained at the requisition layer.
    Type: Application
    Filed: March 17, 2021
    Publication date: September 22, 2022
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV
  • Publication number: 20220292386
    Abstract: Embodiments of this disclosure include a method and system for machine learning based evaluation of user experience on information technology (IT) support service. The method may include obtaining a field data of an IT support service ticket and obtaining a multi-score prediction engine. The method may further include predicting metric scores of a plurality of IT support service metrics for the support service ticket based on the field data by executing the multi-score prediction engine. The method may further include obtaining system-defined weights and user-defined weights for the plurality of service metrics and calculating a support service score for the support service ticket based on the metric scores, the system-defined weights, and the user-defined weights. The method may further include evaluating user experience based on the support service score.
    Type: Application
    Filed: March 9, 2021
    Publication date: September 15, 2022
    Inventors: Madhan Kumar Srinivasan, Kishore Kumar Gajula, Gagan Deep Khosla, Kuljeet Singh, Ashish Pant
  • Publication number: 20220237208
    Abstract: The present disclosure relates to systems and methods for carrying out predictive analysis where a plurality of data sets may be ingested from a data lake. A data analyzer may tag the ingested data sets, detect redundant occurrence of multiple attributes such as, a row, a column, and a list in the tagged data set. The data analyzer may eliminate the detected redundant multiple attributes. Further, a model selector and evaluator may execute a machine learning (ML) model to conduct predictive analysis on the data set. The execution may be done based on a predefined set of instructions stored in a database. The executed ML model may be validated upon determining that the predictive analysis yields a positive response for the transformed data set.
    Type: Application
    Filed: January 22, 2021
    Publication date: July 28, 2022
    Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar SRINIVASAN, Guruprasad Pv, Samba Sivachari Rage
  • Patent number: 11334590
    Abstract: A system may support multiple tier serverless data foundation creation to support large data set processing. At a data ingestion tier, data ingestion serverless tasks may receive source data for processing. The data integration serverless tasks may filter and group the source data into file-object stored items. Further, data integration serverless tasks may capture metadata that, when paired with the file-object stored items, establishes the data foundation. The data foundation facilitates database-like performance in data operations in a database-less system. At the processing tier, the processing serverless tasks access the data foundation by iterating across the file-object stored items to generate output-object stored items. At the directed storage tier, directed storage serverless tasks capture metadata for the output-object stored items to establish an output data foundation or prepare the output data for storage in a data warehouse.
    Type: Grant
    Filed: December 28, 2018
    Date of Patent: May 17, 2022
    Assignee: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Arun Purushothaman, Vijaya Tapaswi Achanta
  • Patent number: 11334630
    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: Grant
    Filed: February 19, 2020
    Date of Patent: May 17, 2022
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Guruprasad PV, Manish Sharma Kolachalam
  • Patent number: 11321142
    Abstract: A system includes a multi-layer capacity configuration optimization (CCO) stack to generate a token containing prescriptions for optimize capacity configuration of a database container in a NoSQL database cloud service. The system may aggregate the capacity utilization data; predict, based on the aggregated capacity utilization data, respective prediction-based processing capacity utilizations for the database container; determine a target processing capacity utilization value from the prediction-based processing capacity utilizations; calculate respective provisioned processing capacity utilizations based on the target processing capacity utilization value; evaluate a consumption metric based on the prediction-based processing capacity utilizations and the provisioned processing capacity utilizations; select one of the predetermined capacity modes as a recommended capacity mode for the database container based on the consumption metric.
    Type: Grant
    Filed: June 15, 2020
    Date of Patent: May 3, 2022
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Madhan Kumar Srinivasan, Kishore Kumar Gajula
  • Patent number: 11321343
    Abstract: Embodiments operate a multi-tenant cloud system. At a first data center, embodiments authenticate a first client and store resources that correspond to the first client, the first data center in communication with a second data center that is configured to authenticate the first client. Embodiments divide the resources into base data and regular data, where the base data is a minimum data needed to allow the resources to be available to the first client at the second data center. Embodiments store the base data on a cloud storage in a base data export file and store the regular data on the cloud storage in a regular data export file. Embodiments export the base data export file to the second data center and when the exporting the base data export file has completed, exports the regular data export file to the second data center.
    Type: Grant
    Filed: August 29, 2019
    Date of Patent: May 3, 2022
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Sudhir Kumar Srinivasan, Balakumar Balu, Venkateswara Reddy Medam, Kuang-Yu Shih, Fannie Ho
  • 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: 11308132
    Abstract: A system stores and uses object relationships in a multi-tenant cloud-based identity and access management (IAM) system by: defining a schema for storing related objects, where the schema includes reference attributes indicative of relationships between the related objects in a database, and the schema defines a relationship type and a persistence scope for each reference attribute; constructing an in-memory representation of the related objects and their relationships based on the schema, where the in-memory representation indicates the relationship type and the persistence scope for each reference attribute; and using the in-memory representation of the related objects to perform an IAM service for a client of the multi-tenant cloud-based IAM system.
    Type: Grant
    Filed: May 29, 2018
    Date of Patent: April 19, 2022
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Sudhir Kumar Srinivasan, Shruthi Chikkanna, Nikhil Yograj Vaishnavi, Xiaoxiao Xu, Gregg Wilson, Venkateswara Reddy Medam
  • Patent number: 11293954
    Abstract: Aspects of the disclosure provide for a circuit. In some examples, the circuit includes a Zener diode, a first current source, a first n-type field effect transistor (FET), a first inverter circuit, and a second current source. The Zener diode has a cathode coupled to a first node and an anode coupled to a second node. The first current source has a first terminal coupled to the second node and a second terminal coupled to a ground terminal. The first n-type FET has a gate terminal coupled to the second node, a source terminal coupled to the ground terminal, and a drain terminal coupled to a third node. The first inverter circuit has an input coupled to the third node and an output coupled to a fourth node. The second current source has a first terminal coupled to a fifth node and a second terminal coupled to the third node.
    Type: Grant
    Filed: March 25, 2019
    Date of Patent: April 5, 2022
    Assignee: TEXAS INSTRUMENTS INCORPORATED
    Inventors: Naman Gupta, Rajat Chauhan, Santhosh Kumar Srinivasan
  • Publication number: 20220014421
    Abstract: Embodiments operate a multi-tenant cloud system. At a first data center, embodiments authenticate a first client corresponding to a first tenant ID and store resources that correspond to the first client, the first data center in communication with a second data center that is configured to authenticate the first client and replicate the resources. The first data center receives an Application Programming Interface (“API”) request for the first client corresponding to a change to the resources, and generates a change log and corresponding change event message in response to the API request. Embodiments compute a first hash corresponding to the first tenant ID of the change log to determine a first partition of a first queue at the first data center. The first data center pushes the change event message to the second data center via an API call.
    Type: Application
    Filed: September 27, 2021
    Publication date: January 13, 2022
    Inventors: Venkateswara Reddy MEDAM, Fannie HO, Kuang-Yu SHIH, Balakumar BALU, Sudhir Kumar SRINIVASAN
  • 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: 20210342197
    Abstract: A system includes a multi-layer capacity configuration optimization (CCO) stack to generate a token containing prescriptions for optimize capacity configuration of a database container in a NoSQL database cloud service. The system may aggregate the capacity utilization data; predict, based on the aggregated capacity utilization data, respective prediction-based processing capacity utilizations for the database container; determine a target processing capacity utilization value from the prediction-based processing capacity utilizations; calculate respective provisioned processing capacity utilizations based on the target processing capacity utilization value; evaluate a consumption metric based on the prediction-based processing capacity utilizations and the provisioned processing capacity utilizations; select one of the predetermined capacity modes as a recommended capacity mode for the database container based on the consumption metric.
    Type: Application
    Filed: June 15, 2020
    Publication date: November 4, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Kishore Kumar Gajula
  • Patent number: 11165634
    Abstract: Embodiments include a multi-tenant cloud system with a first data center and a second remote data center. The first data center authenticates a first client and stores resources that correspond to the first client, and is in communication with the second data center. The second data center authenticates the first client and replicates the resources. The first data center receives a write request for the first client, writes the write request and generates change event messages in a first order. The first data center pushes the change event messages to the second data center via REST API calls. In response to receiving the change event messages, the second data center is configured to write the change event messages in the first order to its local database.
    Type: Grant
    Filed: August 22, 2018
    Date of Patent: November 2, 2021
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Venkateswara Reddy Medam, Fannie Ho, Kuang-Yu Shih, Balakumar Balu, Sudhir Kumar Srinivasan
  • 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: 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: 20210288880
    Abstract: A multi-layer cluster node optimization (CNO) stack may generate a token containing cluster node optimization prescriptions for detaching nodes from a storage cluster. A prescriptive engine layer of the CNO stack may select target computing resource nodes from a selected cluster based on the utilization tracking data, the optimization metric thresholds, and the CNO interval; utilize a prediction engine to predict respective storage utilizations over a next operation cycle for the nodes of the selected cluster; generate an aggregated storage utilization prediction for the selected cluster based on the predicted storage utilizations; determine a network traffic coefficient for the selected cluster based on the network traffic data; perform a cluster determination whether to execute a cluster node optimization for the selected cluster based on the aggregated storage utilization prediction and the network traffic coefficient; and generate a CNO token based on the cluster determination.
    Type: Application
    Filed: March 13, 2020
    Publication date: September 16, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Madhan Kumar Srinivasan, Kishore Kumar Gajula, Samba Sivachari Rage