Abstract: Technologies are disclosed for local and distributed function based dynamic traffic management for network services. A service host executes a network service and provides a service framework that includes one or more handlers. When a request is received for the service, one of the handlers assigns a classification to the request. The handler then provides the classification to a dynamic function based traffic controller. The controller determines whether the network service is to process the request based on the classification of the request, metrics associated with the network service, and a local traffic management policy. If the controller determines that the network service is not to process the request, the request is rejected. Otherwise, the request is passed to the network service for processing. Metrics can also be provided from the service host to a distributed performance monitoring system for use in managing network traffic at a fleet level.

Abstract: Technologies are disclosed for local and distributed function based dynamic traffic management for network services. A service host executes a network service and provides a service framework that includes one or more handlers. When a request is received for the service, one of the handlers assigns a classification to the request. The handler then provides the classification to a dynamic function based traffic controller. The controller determines whether the network service is to process the request based on the classification of the request, metrics associated with the network service, and a local traffic management policy. If the controller determines that the network service is not to process the request, the request is rejected. Otherwise, the request is passed to the network service for processing. Metrics can also be provided from the service host to a distributed performance monitoring system for use in managing network traffic at a fleet level.

Abstract: Technologies are disclosed for local and distributed function based dynamic traffic management for network services. A service host executes a network service and provides a service framework that includes one or more handlers. When a request is received for the service, one of the handlers assigns a classification to the request. The handler then provides the classification to a dynamic function based traffic controller. The controller determines whether the network service is to process the request based on the classification of the request, metrics associated with the network service, and a local traffic management policy. If the controller determines that the network service is not to process the request, the request is rejected. Otherwise, the request is passed to the network service for processing. Metrics can also be provided from the service host to a distributed performance monitoring system for use in managing network traffic at a fleet level.

Abstract: Technologies are disclosed for local and distributed function based dynamic traffic management for network services. A service host executes a network service and provides a service framework that includes one or more handlers. When a request is received for the service, one of the handlers assigns a classification to the request. The handler then provides the classification to a dynamic function based traffic controller. The controller determines whether the network service is to process the request based on the classification of the request, metrics associated with the network service, and a local traffic management policy. If the controller determines that the network service is not to process the request, the request is rejected. Otherwise, the request is passed to the network service for processing. Metrics can also be provided from the service host to a distributed performance monitoring system for use in managing network traffic at a fleet level.

Abstract: Technologies are disclosed for local and distributed function based dynamic traffic management for network services. A service host executes a network service and provides a service framework that includes one or more handlers. When a request is received for the service, one of the handlers assigns a classification to the request. The handler then provides the classification to a dynamic function based traffic controller. The controller determines whether the network service is to process the request based on the classification of the request, metrics associated with the network service, and a local traffic management policy. If the controller determines that the network service is not to process the request, the request is rejected. Otherwise, the request is passed to the network service for processing. Metrics can also be provided from the service host to a distributed performance monitoring system for use in managing network traffic at a fleet level.

Abstract: The present invention discloses a method of testing an analog-to-digital converter (ADC). The method includes receiving a series of analog signals from a tester site, converting the series of analog signals to a series of digital code words using an ADC, evaluating the ADC based on the series of digital code words using an ADC test setup and generating an output signal identifying whether the ADC has passed the testing.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Determining one or more concepts associated with a query is disclosed. A query is received. A list of concepts and associated scores is received. The concepts fit within a concept hierarchy. A density function is used to evaluate the received concepts. One or more concepts are associated with the query based at least in part on the results of the density function.

Abstract: Determining one or more concepts associated with a query is disclosed. A query is received. A list of concepts and associated scores is received. The concepts fit within a concept hierarchy. A density function is used to evaluate the received concepts. One or more concepts are associated with the query based at least in part on the results of the density function.

Abstract: Exemplary embodiments allow performance of stream computations on real-time data streams using one or more map operations and/or one or more update operations. A map operation is a stream computation in which stream events in one or more real-time data streams are processed in a real-time manner to generate zero, one or more new stream events. An update operation is a stream computation in which stream events in one or more real-time data streams are processed in a real-time manner to create or update one or more static “slate” data structures that are stored in a durable manner.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Disclosed are systems and methods for processing events in an event stream using a map-update application. The events may be embodied as a key-attribute pair. An event is processed by one or more instances implementing either a map or an update function. A map function receives an input event from the event stream and publishes one or more events to the event stream. An update function receives an event and updates a corresponding slate and publishes zero or more events. Systems and methods are also disclosed herein for implementing a map-update application in a multithreaded architecture and for handling overloading of a particular thread or node. Systems and methods for providing access to slates updated according to update operations are also disclosed.

Abstract: Exemplary embodiments allow performance of stream computations on real-time data streams using one or more map operations and/or one or more update operations. A map operation is a stream computation in which stream events in one or more real-time data streams are processed in a real-time manner to generate zero, one or more new stream events. An update operation is a stream computation in which stream events in one or more real-time data streams are processed in a real-time manner to create or update one or more static “slate” data structures that are stored in a durable manner.