Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in-line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in-line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: A network controller maintains network availability between a pair of endpoints. The controller detects a topology of a computer network connecting endpoints. The controller determines a metric of availability between a first endpoint and a second endpoint. The metric of availability is based on non-overlapping paths between the first endpoint and the second endpoint. Responsive to a determination that the metric of availability satisfies a predetermined criterion, the controller adjusts a path between the first endpoint and the second endpoint.

Abstract: Described herein is a system and techniques for implementing a system that enables exchange of user information between retail and advertising domains while maintaining data security and privacy requirements. In some embodiments, a landing page is generated in response to a user interaction with a user interface element. The landing page is generated within the retail domain while the advertisement is in an advertising domain. The landing page, while in the retail domain, can access stored user information from the retail website and pre-fill forms of the landing page which a user can verify and submit to the advertising, thereby sharing the user information into the advertising domain.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in-line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in—line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: A first leaf switch may receive from a first host, a request for a second host that is not known at the first leaf switch. The first host may be within a first End Point Group (EPG) and the second host being within a second EPG. The first EPG and the second EPG may be in a Bridge Domain (BD). Flood in encapsulation may be enabled for the first EPG and for the second EPG. Next, the first leaf switch may flood the request locally in the first EPG and to a spine switch with a VNID of the first EPG. The spine switch may then flood the request to a second leaf switch where the BD is present. The second leaf switch may send a glean request for the second host, receive, in response to sending the glean request, a reply, and learn the second host locally in response to receiving the reply.

Abstract: Computer-implemented methods and systems construct a calibrated operation-centric first-principles model suitable for online deployment to monitor, predict, and control real-time plant operations. The methods and systems identify a plant-wide first-principles model configured for offline use and select a modeled operating unit contained in the plant-wide model. The methods and systems convert the plant-wide model to an operation-centric first-principles model of the selected modeled operating unit. The methods and systems recalibrate the operation-centric model to function using real-time measurements collected by physical instruments of the operating unit at the plant. The recalibration may include reconciling flow and temperature, estimating feed compositions, and tuning liquid and vapor traffic flow in the model. The methods and systems deploy the operation-centric model to calculate KPIs (Key Performance Indicators) using real-time measurements.

Abstract: Computer-based methods and system perform root-cause analysis on an industrial process. A processor executes a hybrid first-principles and inferential model to generate KPIs for the industrial process using uploaded process data as variables. The processor selects a subset of the KPIs to represent an event occurring in the industrial process, and divides the selected data into time series. The system and methods select time intervals from the time series based on data variability and perform a cross-correlation between the loaded process variables and the selected time intervals, resulting in a cross-correlation score for each loaded process variable. Precursor candidates from the loaded process variables are selected based on the cross-correlation scores, and a strength of correlation score is obtained for each precursor candidate. The methods and system select root-cause variables from the selected precursor candidates based on the strength of correlation scores, and analyze the root-cause of the event.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in—line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in-line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: Embodiments are directed to computer methods and systems that construct a calibrated operation-centric first-principles model suitable for online deployment to monitor, predict, and control real-time plant operations. The methods and systems identify a plant-wide first-principles model configured for offline use and select a modeled operating unit contained in the plant-wide model. The methods and systems convert the plant-wide model to an operation-centric first-principles model of the selected modeled operating unit. The methods and systems recalibrate the operation-centric model to function using real-time measurements collected by physical instruments of the operating unit at the plant. The recalibration may include reconciling flow and temperature, estimating feed compositions, and tuning liquid and vapor traffic flow in the model.

Abstract: A method, apparatus, and computer program product for increasing efficiency in a plant by creating a planning model for said plant comprising a plurality of runtime models stored in a database. Each runtime model corresponds to a reactor in the plant and mimics real world behavior of the reactor by identifying the mathematical relationships of the inputs and outputs of the reactor. Each runtime model further comprises a set of tuning factors, which allows the user to adjust the runtime model to more closely align with the user's desired output or otherwise account for real-life plant activity. By properly creating and utilizing a plurality of runtime models and implementing them into a planning model, a user can increase efficiency of the plant by optimizing product output, forcing the plant to balance materials-in and materials-out, or forcing the plant to stoichiometrically balance elements going in, and coming out of the plant or reactor.

Abstract: Systems, methods, and computer-readable media for improving debugging and troubleshooting of datacenter networks, and more particularly improving the speed of forwarding/data path related problems without going into ASIC level debugging. A switch could, for example, have a processor which communicates with an ASIC. The processor can receive flow information and a notification from the ASIC, the notification indicating a predefined error condition has been identified in a packet. The processor can modify the ASIC programming based on the notification, such that the ASIC records additional, more-detailed, flow information for the switch. The processor can then receive, from the modified ASIC, the additional flow information. The additional flow information can then be used (either by the processor or by an operator) to identify the exact reason for the errors in the flow path.

Abstract: Computer-based methods and system perform root-cause analysis on an industrial process. A processor executes a hybrid first-principles and inferential model to generate KPIs for the industrial process using uploaded process data as variables. The processor selects a subset of the KPIs to represent an event occurring in the industrial process, and divides the selected data into time series. The system and methods select time intervals from the time series based on data variability and perform a cross-correlation between the loaded process variables and the selected time intervals, resulting in a cross-correlation score for each loaded process variable. Precursor candidates from the loaded process variables are selected based on the cross-correlation scores, and a strength of correlation score is obtained for each precursor candidate. The methods and system select root-cause variables from the selected precursor candidates based on the strength of correlation scores, and analyze the root-cause of the event.

Abstract: Computer-based methods and system perform root-cause analysis on an industrial process. A processor executes a hybrid first-principles and inferential model to generate KPIs for the industrial process using uploaded process data as variables. The processor selects a subset of the KPIs to represent an event occurring in the industrial process, and divides the selected data into time series. The system and methods select time intervals from the time series based on data variability and perform a cross-correlation between the loaded process variables and the selected time intervals, resulting in a cross-correlation score for each loaded process variable. Precursor candidates from the loaded process variables are selected based on the cross-correlation scores, and a strength of correlation score is obtained for each precursor candidate. The methods and system select root-cause variables from the selected precursor candidates based on the strength of correlation scores, and analyze the root-cause of the event.

Abstract: Disclosed is a method for continuous in-line monitoring of data-centric traffic to guarantee application performance. The method includes, in each switch of a plurality of switches in a network fabric, grouping all packets entering each respective switch of the plurality of switches based on either 5-tuple applications or EPG based applications, collecting performance statistics at every hop in the network fabric across all flows in-line in a flow table maintained in each respective switch and periodically exporting the performance statistics to analysis module.

Abstract: Systems, methods, and computer-readable media for improving debugging and troubleshooting of datacenter networks, and more particularly improving the speed of forwarding/data path related problems without going into ASIC level debugging. A switch could, for example, have a processor which communicates with an ASIC. The processor can receive flow information and a notification from the ASIC, the notification indicating a predefined error condition has been identified in a packet. The processor can modify the ASIC programming based on the notification, such that the ASIC records additional, more-detailed, flow information for the switch. The processor can then receive, from the modified ASIC, the additional flow information. The additional flow information can then be used (either by the processor or by an operator) to identify the exact reason for the errors in the flow path.

Abstract: The present invention is directed to computer-based methods and system to perform root-cause analysis on an industrial process. The methods and system load process data for an industrial process from a historian database and build a hybrid first-principles and inferential model. The methods and system then executes the hybrid model to generate KPIs for the industrial process using the loaded process variables. The methods and system then selects a subset of the KPIs to represent an event occurring in the industrial process, and divides the data for the subset into multiple subset of time series. The system and methods select time intervals from the time series based on the data variability in the selected time intervals and perform a cross-correlation between the loaded process variables and the selected time interval, resulting in a cross-correlation score for each loaded process variable.

Abstract: A method, apparatus, and computer program product for increasing efficiency in a plant by creating a planning model for said plant comprising a plurality of runtime models stored in a database. Each runtime model corresponds to a reactor in the plant and mimics real world behavior of the reactor by identifying the mathematical relationships of the inputs and outputs of the reactor. Each runtime model further comprises a set of tuning factors, which allows the user to adjust the runtime model to more closely align with the user's desired output or otherwise account for real-life plant activity. By properly creating and utilizing a plurality of runtime models and implementing them into a planning model, a user can increase efficiency of the plant by optimizing product output, forcing the plant to balance materials-in and materials-out, or forcing the plant to stoichiometrically balance elements going in, and coming out of the plant or reactor.