Abstract: In general, techniques are described for providing network device modeling in preconfigured network modeling environments. A device comprising a memory and a processor may be configured to perform the techniques. The processor may interface with a network device within the preconfigured network environment to iteratively adapt pre-defined configuration objects of the network device. The processor may conduct, for each iteration of the adaptation of the pre-defined configuration objects, a simulation to collect a simulation dataset representative of an operating state of the network device. The processor may generate, based on the operational data, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device. The memory may store the model.

Abstract: In general, techniques are described for automated network device model creation using randomized test beds. A device comprising a processor may be configured to perform the techniques. The processor may generate, based on simulation configuration files, configuration objects for performing a plurality of simulation iterations with respect to the network device operating within a test environment. Each of the simulation iterations may be configured to randomly assign parameters within the test environment. The driver may conduct, based on the configuration objects, each of the simulation iterations within the test environment to collect simulation datasets representative of operating states of the network device. The analytics module may perform machine learning with respect to each of the simulation datasets to generate a model that predicts, responsive to configuration parameters, an operating state of the network device when configured with the configuration parameters for the network device.

Abstract: In general, techniques are described for providing diversity in simulation datasets during modeling. A device comprising a memory and a processor may be configured to perform the techniques. The memory may store simulation configuration files for conducting simulations of the network device within a test environment. The processor may conduct, based on the simulation configuration files, each of the simulations with respect to the network device to collect corresponding simulation datasets indicative of an operating state of the network device. The processor may determine a level of similarity between the simulation datasets, and select, responsive to a comparison of the level of similarity to a diversity threshold, a subset of the simulation datasets. The processor may generate, based on the selected subset of the simulation datasets, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device.

Abstract: In general, techniques are described for providing diversity in simulation datasets during modeling. A device comprising a memory and a processor may be configured to perform the techniques. The memory may store simulation configuration files for conducting simulations of the network device within a test environment. The processor may conduct, based on the simulation configuration files, each of the simulations with respect to the network device to collect corresponding simulation datasets indicative of an operating state of the network device. The processor may determine a level of similarity between the simulation datasets, and select, responsive to a comparison of the level of similarity to a diversity threshold, a subset of the simulation datasets. The processor may generate, based on the selected subset of the simulation datasets, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device.

Abstract: In general, techniques are described for automated network device model creation using randomized test beds. A device comprising a processor may be configured to perform the techniques. The processor may generate, based on simulation configuration files, configuration objects for performing a plurality of simulation iterations with respect to the network device operating within a test environment. Each of the simulation iterations may be configured to randomly assign parameters within the test environment. The driver may conduct, based on the configuration objects, each of the simulation iterations within the test environment to collect simulation datasets representative of operating states of the network device. The analytics module may perform machine learning with respect to each of the simulation datasets to generate a model that predicts, responsive to configuration parameters, an operating state of the network device when configured with the configuration parameters for the network device.

Abstract: In general, techniques are described for providing network device modeling in preconfigured network modeling environments. A device comprising a memory and a processor may be configured to perform the techniques. The processor may interface with a network device within the preconfigured network environment to iteratively adapt pre-defined configuration objects of the network device. The processor may conduct, for each iteration of the adaptation of the pre-defined configuration objects, a simulation to collect a simulation dataset representative of an operating state of the network device. The processor may generate, based on the operational data, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device. The memory may store the model.

Abstract: In general, techniques are described for providing diversity in simulation datasets during modeling. A device comprising a memory and a processor may be configured to perform the techniques. The memory may store simulation configuration files for conducting simulations of the network device within a test environment. The processor may conduct, based on the simulation configuration files, each of the simulations with respect to the network device to collect corresponding simulation datasets indicative of an operating state of the network device. The processor may determine a level of similarity between the simulation datasets, and select, responsive to a comparison of the level of similarity to a diversity threshold, a subset of the simulation datasets. The processor may generate, based on the selected subset of the simulation datasets, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device.

Abstract: In general, techniques are described for providing diversity in simulation datasets during modeling. A device comprising a memory and a processor may be configured to perform the techniques. The memory may store simulation configuration files for conducting simulations of the network device within a test environment. The processor may conduct, based on the simulation configuration files, each of the simulations with respect to the network device to collect corresponding simulation datasets indicative of an operating state of the network device. The processor may determine a level of similarity between the simulation datasets, and select, responsive to a comparison of the level of similarity to a diversity threshold, a subset of the simulation datasets. The processor may generate, based on the selected subset of the simulation datasets, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device.

Abstract: One example method includes receiving, by a central analytics system, a query for traffic flow data associated with a geographically distributed network of network devices, outputting, by the central analytics system, the query to a plurality of analytics pods, wherein each of the plurality of analytics pods is coupled to a storage unit of a network device within the geographically distributed network, and, responsive to outputting the query, receiving, by the central analytics system and from the plurality of analytics pods, results of the query, wherein the results include at least the traffic flow data from the plurality of analytics pods based on the query.

Abstract: An application on a device includes multiple experience modules that each implement a set of features when the application is running on the device. Each of the multiple experience modules includes a first component that includes code specific to a particular type of the device, and a second component that includes code that is common across multiple types of devices. Update packages changing individual ones of the multiple experience modules can be received from a deployment service and installed on the device.

Abstract: One example method includes receiving, by a central analytics system, a query for traffic flow data associated with a geographically distributed network of network devices, outputting, by the central analytics system, the query to a plurality of analytics pods, wherein each of the plurality of analytics pods is coupled to a storage unit of a network device within the geographically distributed network, and, responsive to outputting the query, receiving, by the central analytics system and from the plurality of analytics pods, results of the query, wherein the results include at least the traffic flow data from the plurality of analytics pods based on the query.

Abstract: In embodiments of current device location advertisement distribution, a mobile network operator receives media content from a content service and can then communicate the media content to a client device via a wireless distribution point. A device location service determines that a current location of the client device is not within a geographic region associated with the client device, and updates the current location of the client device from location data that identifies the current location of the client device. The media content can then be updated for distribution to the client device along with advertisements that correspond to an advertising locale, which includes the current location of the client device.

Abstract: A network server that includes at least a processor is configured to receive, from a first network, a trigger event received in the first network from a non web-enabled device configured to communicate the trigger event to the first network, wherein the trigger event includes a designation of at least one file to be transferred. The network server is further configured to transmit a notification that includes the designation to a second network based on the trigger event, the second network being a web-enabled network communicatively coupled to at least a first web-enabled peer node that is capable of receiving the notification.

Abstract: In embodiments of current device location advertisement distribution, a mobile network operator receives media content from a content service and can then communicate the media content to a client device via a wireless distribution point. A device location service determines that a current location of the client device is not within a geographic region associated with the client device, and updates the current location of the client device from location data that identifies the current location of the client device. The media content can then be updated for distribution to the client device along with advertisements that correspond to an advertising locale, which includes the current location of the client device.

Abstract: In embodiments of current device location advertisement distribution, a mobile network operator receives television content from a content service and can then communicate the television content to a client device via a wireless distribution point. A device location service determines that a current location of the client device is not within a geographic region associated with the client device, and updates the current location of the client device from location data that identifies the current location of the client device. The television content can then be updated for distribution to the client device along with advertisements that correspond to an advertising locale, which includes the current location of the client device.

Abstract: In embodiments of wireless distribution system proxy caches, a mobile network operator receives requests for television content from client devices, and communicates one of the requests to a content service that provides the television content for distribution to the client devices. Proxy caches are implemented to cache content data of the television content prior to the cached content data of the television content being wirelessly communicated to the client devices. The proxy caches are located at wireless distribution points of the mobile network operator, and the wireless distribution points communicate the cached content data of the television content from the proxy caches to the client devices.

Abstract: Media units are stored in a buffer, wherein an importance rating is assigned to each of the media units. At least some of the media units are selectively flushed from the buffer based on the importance rating.

Abstract: Media units are stored in a buffer, wherein an importance rating is assigned to each of the media units. At least some of the media units are selectively flushed from the buffer based on the importance rating.

Abstract: Controllable device selection based on controller location is described. In embodiments, a companion utility is executed by a portable device to interface the portable device with a selected one of multiple controllable devices via a wireless network. A location of the portable device can be determined based on a positioning unit that is integrated with the portable device. A controllable device can then be selected that is proximate the location of the portable device for input control of the controllable device via the wireless network.

Abstract: Editable bookmarks shared via a social network are described. In embodiments, a bookmark is received from a client device at a media content service. The bookmark corresponds to a media asset and includes an identifier of the media asset. Metadata associated with the media asset is added to the bookmark to generate an editable bookmark. A bookmark invitation is also received from the client device, and the bookmark invitation is directed to social network contacts of a user of the client device. The editable bookmark can then be communicated to receiving client devices of the respective social network contacts identified by the bookmark invitation, and a receiving client device can initiate playback of the media asset that corresponds to the editable bookmark. Further, the editable bookmark can be updated when additional data associated with the media asset is received from a social network contact via a respective client device.