Patents by Inventor Jiahan Wang
Jiahan Wang 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).
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Patent number: 11916764Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.Type: GrantFiled: January 9, 2023Date of Patent: February 27, 2024Assignee: SPLUNK INC.Inventors: Pradeep Baliganapalli Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Patent number: 11836579Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and send the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.Type: GrantFiled: September 17, 2019Date of Patent: December 5, 2023Assignee: SPLUNK INC.Inventors: Pradeep Baliganapalli Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Patent number: 11720537Abstract: Systems and methods are disclosed for scalable bucket merging in a data intake and query system. Various components of a bucket manager can be used to monitor recently-created buckets of data in common storage that are associated with a particular tenant and a particular index, apply a comprehensive bucket merge policy to determine groups of buckets that qualify for merging, merge those group of buckets into merged buckets to be stored in the common storage, and update any information associated with the merged buckets and pre-merged buckets. These components may be shared across multiple tenants, and some of these components may be dynamically scalable based on need. This approach may also provide many additional benefits, including improved search performance from merged buckets, efficient resource utilization associated with discriminate merging, and redundancy in case of component failure.Type: GrantFiled: April 29, 2022Date of Patent: August 8, 2023Assignee: Splunk Inc.Inventors: Tameem Anwar, Tianyi Gou, Alexandros Batsakis, Abhinav Prasad Nekkanti, Sai Krishna Sajja, Jiahan Wang
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Patent number: 11610156Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.Type: GrantFiled: August 9, 2021Date of Patent: March 21, 2023Assignee: SPLUNK INC.Inventors: Pradeep Baliganapalli Nagaraju, Steve Zhang, Jiahan Wang, Adam Jamison Oliner, Erick Anthony Dean
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Patent number: 11595274Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.Type: GrantFiled: December 23, 2019Date of Patent: February 28, 2023Assignee: SPLUNK INC.Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Patent number: 11552866Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.Type: GrantFiled: December 23, 2019Date of Patent: January 10, 2023Assignee: SPLUNK INC.Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Publication number: 20220261385Abstract: Systems and methods are disclosed for scalable bucket merging in a data intake and query system. Various components of a bucket manager can be used to monitor recently-created buckets of data in common storage that are associated with a particular tenant and a particular index, apply a comprehensive bucket merge policy to determine groups of buckets that qualify for merging, merge those group of buckets into merged buckets to be stored in the common storage, and update any information associated with the merged buckets and pre-merged buckets. These components may be shared across multiple tenants, and some of these components may be dynamically scalable based on need. This approach may also provide many additional benefits, including improved search performance from merged buckets, efficient resource utilization associated with discriminate merging, and redundancy in case of component failure.Type: ApplicationFiled: April 29, 2022Publication date: August 18, 2022Inventors: Tameem Anwar, Tianyi Gou, Alexandros Batsakis, Abhinav Prasad Nekkanti, Sai Krishna Sajja, Jiahan Wang
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Patent number: 11334543Abstract: Systems and methods are disclosed for scalable bucket merging in a data intake and query system. Various components of a bucket manager can be used to monitor recently-created buckets of data in common storage that are associated with a particular tenant and a particular index, apply a comprehensive bucket merge policy to determine groups of buckets that qualify for merging, merge those group of buckets into merged buckets to be stored in the common storage, and update any information associated with the merged buckets and pre-merged buckets. These components may be shared across multiple tenants, and some of these components may be dynamically scalable based on need. This approach may also provide many additional benefits, including improved search performance from merged buckets, efficient resource utilization associated with discriminate merging, and redundancy in case of component failure.Type: GrantFiled: October 18, 2019Date of Patent: May 17, 2022Assignee: Splunk Inc.Inventors: Tameem Anwar, Tianyi Gou, Alexandros Batsakis, Abhinav Prasad Nekkanti, Sai Krishna Sajja, Jiahan Wang
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Patent number: 11087236Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.Type: GrantFiled: July 26, 2017Date of Patent: August 10, 2021Assignee: SPLUNK INC.Inventors: Pradeep Baliganapalli Nagaraju, Steve Zhang, Jiahan Wang, Adam Jamison Oliner, Erick Anthony Dean
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Patent number: 10536351Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating timestamped events, where the timestamped events include raw data generated by electronic device. The technique can further include obtaining results by performing a operation on the timestamped events, in accordance with instructions. The technique can further include sending the results or indicia thereof over a network to a server computer system, and receiving back new instructions generated by the server computer system based on the sent results. Lastly, the technique can include performing a new operation on timestamped events including raw data generated based by the electronic device, where the new operation can be performed in accordance with the new instructions to obtain new results.Type: GrantFiled: July 29, 2016Date of Patent: January 14, 2020Assignee: SPLUNK INC.Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Publication number: 20200012966Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and sending the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.Type: ApplicationFiled: September 17, 2019Publication date: January 9, 2020Inventors: Pradeep Baliganapalli Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Patent number: 10460255Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating raw data based on inputs to the electronic device, and sending the raw data or data items over a network to a server computer system. The sent raw data or the data items can include training data. The technique can further include receiving global model data from the server computer system over the network. The global model data may have been derived from the training data in accordance with a machine learning process. The technique can further include generating an updated local model by updating a local model associated with the electronic device based on the received global model data, and processing local data based on the updated local model to generate output data. The local data can include raw data or data items generated based on inputs to the electronic device.Type: GrantFiled: July 29, 2016Date of Patent: October 29, 2019Assignee: SPLUNK INC.Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Publication number: 20180032908Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating raw data based on inputs to the electronic device, and sending the raw data or data items over a network to a server computer system. The sent raw data or the data items can include training data. The technique can further include receiving global model data from the server computer system over the network. The global model data may have been derived from the training data in accordance with a machine learning process. The technique can further include generating an updated local model by updating a local model associated with the electronic device based on the received global model data, and processing local data based on the updated local model to generate output data. The local data can include raw data or data items generated based on inputs to the electronic device.Type: ApplicationFiled: July 29, 2016Publication date: February 1, 2018Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Publication number: 20180034715Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating timestamped events, where the timestamped events include raw data generated by electronic device. The technique can further include obtaining results by performing a operation on the timestamped events, in accordance with instructions. The technique can further include sending the results or indicia thereof over a network to a server computer system, and receiving back new instructions generated by the server computer system based on the sent results. Lastly, the technique can include performing a new operation on timestamped events including raw data generated based by the electronic device, where the new operation can be performed in accordance with the new instructions to obtain new results.Type: ApplicationFiled: July 29, 2016Publication date: February 1, 2018Inventors: Pradeep B. Nagaraju, Adam Jamison Oliner, Brian Matthew Gilmore, Erick Anthony Dean, Jiahan Wang
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Publication number: 20180032915Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.Type: ApplicationFiled: July 26, 2017Publication date: February 1, 2018Inventors: Pradeep Baliganapalli NAGARAJU, Steve ZHANG, Jiahan WANG, Adam Jamison OLINER, Erick Anthony DEAN