Sriramakrishna Yelisetti

20130132170, May 23, 2013

Nov 18, 2011

13/300409

Sriramakrishna Yelisetti - Sunnyvale CA, US
Ashutosh A. Malegaonkar - Milpitas CA, US

G06Q 30/02

705 144

An example method is provided and includes analyzing a digital advertisement configured for display on a digital sign; identifying a tag event that includes a keyword provided in the digital advertisement; identifying a time interval associated with the tag event; and recording the tag event and the time interval in a log. In more specific embodiments, the tag event further comprises an identification of a speaker in the digital advertisement. The digital advertisement can be identified by a token that may be associated with a hash having a time derived attribute.

20200210432, Jul 2, 2020

Dec 31, 2018

16/236762

- Schenectady NY, US
Sriramakrishna YELISETTI - San Ramon CA, US
Ramana Venkatesh SIVASUBRAMANIAN - San Ramon CA, US
Arvind SINGH - San Ramon CA, US

G06F 16/2455
G06F 16/21
G06F 16/22

The example embodiments are directed to a system and method for re-partitioning a storage for asset data based on a change in the asset data. In one example, the method may include one or more of monitoring asset data that is being stored in a storage device having a predetermined partitioning scheme, identifying a change in a data pattern of the asset data based on the monitoring, modifying the predetermined partitioning scheme into a different partitioning scheme based on the identified change in the data pattern of the asset data, and storing newly received asset data in the storage device based on the different partitioning scheme as a result of the modifying.

20190205182, Jul 4, 2019

Dec 28, 2017

15/856592

- Schenectady NY, US
Sriramakrishna YELISETTI - San Ramon CA, US

G06F 9/54

The example embodiments are directed to a system and method for deploying and monitoring applications within a cloud environment including multiple execution engines. In one example, the system includes a processor to receive application performance data of an application from a runtime environment, the application performance data including performance attributes of the application that are captured while executing the application in the runtime environment, and modify the application performance data into runtime environment agnostic application performance data, and an output to output the runtime environment agnostic application performance data for display via a unified monitoring interface that is configured to display application performance data of different runtime environments. The service described herein provides a layer of abstraction between a client submitting the application and a host platform for the application, and between the host platform and a performance monitoring interface of the application.

20190207867, Jul 4, 2019

Dec 28, 2017

15/856672

- Schenectady NY, US
Sriramakrishna YELISETTI - San Ramon CA, US

H04L 12/911
G06F 9/54

The example embodiments are directed to a system and method for deploying and monitoring applications within a cloud environment including multiple execution engines. In one example, the system includes a network interface configured to receive an application from a client, and a processor configured to determine a cloud services platform, from among a plurality of different cloud services platforms, to be a host platform for the application, and retrieve API information from storage that is unique to the determined cloud services platform and which is to be used for communicating with the determined cloud services platform when executing the application, wherein the processor is further configured to launch an execution of the application via the determined cloud services platform and communicate with the determined cloud services platform on behalf of the executing application based on the retrieved API information.

20180349445, Dec 6, 2018

May 31, 2017

15/610307

- Schenectady NY, US
Ramana Venkatesh Sivasubramanian - Pleasanton CA, US
Sriramakrishna Yelisetti - San Ramon CA, US

G06F 17/30

Methods, systems, and apparatus for prioritizing data are disclosed. A data container is parsed to obtain header information and an asset type is identified based on the header information. A weighted asset priority value and a second weighted priority value are determined. A priority level of the data container is determined based on the weighted asset priority value and the second weighted priority value. An identifier of the data container is appended to a priority queue corresponding to the determined priority level.

20170366356, Dec 21, 2017

Jun 16, 2016

15/184739

- Schenectady NY, US
Venkatesh Sivasubramanian - San Ramon CA, US
Sriramakrishna Yelisetti - San Ramon CA, US

H04L 9/32
H04L 9/08

Methods, systems, and apparatus for ensuring data integrity are disclosed. A data container structure is obtained, the data container structure containing data and a source identifier of a first hardware component. The data container structure is modified, using a header processing device, to include a component signature and an identifier of a second hardware component.

20160212090, Jul 21, 2016

Jan 16, 2015

14/598677

- Schenectady NY, US
Sriramakrishna Yelisetti - San Ramon CA, US
Veera Kishore Reddipalli - San Ramon CA, US
Dave Xiao Feng Chen - San Ramon CA, US

H04L 12/58

A system and method for tracking conversations is disclosed. The method includes receiving an alert, the alert comprising operation information of a machine, determining a user for the alert, determining a first communication medium for a notification message, transmitting the notification message to the user via the first communication medium, the notification message comprising the operation information, storing a record of the notification message in a database in association with a conversation identification, receiving a command message from the user via a second communication medium different from the first communication medium, the command message comprising an instructional command for the machine, transmitting the command message to a control unit of the machine, the control unit being configured to control an operation of the machine based on the instructional command, and storing a record of the command message in the database in association with the conversation identification.