Abstract: Aspects of the disclosure are directed to a central management plane (CMP) of one or more processors for regulating streams of data from each of a number of network nodes of a distributed network. The one or more processors can train and deploy machine learning models across the network nodes, and the CMP can generate policies for each network node. The generated policies specify how a network node is to transmit data to the platform for further training or retraining of the deployed machine learning models. The CMP generates the policies using metric data characterizing each network node and respective streams of input data, and are generated based on a number of objectives, including model output quality of the deployed models, and operational cost to transmit and process streams of data across the distributed network.

Abstract: Aspects of the disclosure are directed to a central management plane (CMP) of one or more processors for regulating streams of data from each of a number of network nodes of a distributed network. The one or more processors can train and deploy machine learning models across the network nodes, and the CMP can generate policies for each network node. The generated policies specify how a network node is to transmit data to the platform for further training or retraining of the deployed machine learning models. The CMP generates the policies using metric data characterizing each network node and respective streams of input data, and are generated based on a number of objectives, including model output quality of the deployed models, and operational cost to transmit and process streams of data across the distributed network.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Abstract: Aspects of the disclosure are directed to a central management plane (CMP) of one or more processors for regulating streams of data from each of a number of network nodes of a distributed network. The one or more processors can train and deploy machine learning models across the network nodes, and the CMP can generate policies for each network node. The generated policies specify how a network node is to transmit data to the platform for further training or retraining of the deployed machine learning models. The CMP generates the policies using metric data characterizing each network node and respective streams of input data, and are generated based on a number of objectives, including model output quality of the deployed models, and operational cost to transmit and process streams of data across the distributed network.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Abstract: Devices, computer-readable media and methods are disclosed for establishing a peer-to-peer network for rerouting network traffic of a telecommunication network during a network disruption. For example, a processing system may detect a network disruption between a first device and a second device of the telecommunication network. The processing system may identify a first peering device having a connection to the first device of the telecommunication network, identify a second peering device having a connection to the second device of the telecommunication network, and establish a peer-to-peer network via at least the first peering device and the second peering device, wherein at least one of the first peering device or the second peering device is a mobile endpoint device configured to operate as a virtual network function. The processing system may then route network traffic between the first device and the second device via the peer-to-peer network.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: Methods, computer-readable media, and devices for instantiating a service provider application of a network service on a customer premises-based device are disclosed. For example, a processing system of a telecommunication network having at least one processor may receive a request for a network service, identify a set of resources for the network service, the set of resources for the network service including at least a first service provider application, and determine that a current configuration of the telecommunication network does not provide the set of resources. The processing system may further reconfigure the telecommunication network to provide the set of resources, the reconfiguring including instantiating the at least the first service provider application of the network service on a customer premises-based device, and deploying the network service to the telecommunication network that is reconfigured.

Abstract: A system for designing and executing control loops in a cloud environment includes a control platform implemented in the cloud environment having a data collection, analytics and events module, a policy module and an application controller module. The system includes a business process management application coupled to the control platform having a control loop designer module for designing a control loop template and a workflow engine for distributing the control loop template. The business process management application is coupled to the data collection analytics and events module of the control platform as well as the policy module in the application controller module to control platform. The control loop is activated by the control platform.

Abstract: Devices, computer-readable media and methods are disclosed for establishing a peer-to-peer network for rerouting network traffic of a telecommunication network during a network disruption. For example, a processing system may detect a network disruption between a first device and a second device of the telecommunication network. The processing system may identify a first peering device having a connection to the first device of the telecommunication network, identify a second peering device having a connection to the second device of the telecommunication network, and establish a peer-to-peer network via at least the first peering device and the second peering device, wherein at least one of the first peering device or the second peering device is a mobile endpoint device configured to operate as a virtual network function. The processing system may then route network traffic between the first device and the second device via the peer-to-peer network.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: Methods, computer-readable media, and devices for instantiating a service provider application of a network service on a customer premises-based device are disclosed. For example, a processing system of a telecommunication network having at least one processor may receive a request for a network service, identify a set of resources for the network service, the set of resources for the network service including at least a first service provider application, and determine that a current configuration of the telecommunication network does not provide the set of resources. The processing system may further reconfigure the telecommunication network to provide the set of resources, the reconfiguring including instantiating the at least the first service provider application of the network service on a customer premises-based device, and deploying the network service to the telecommunication network that is reconfigured.

Abstract: Devices, computer-readable media, and methods for submitting a modified voice input to a service based upon a user intent determined from a voice input in accordance with a voice interface of the service are disclosed. A processing system including at least one processor may obtain a voice input of a user, determine an intent from the voice input, identify a first service, from among a plurality of services, in accordance with the intent, and formulate a first modified voice input from the voice input in accordance with a voice interface of the first service, where each of the services is associated with one of a plurality of different voice interfaces. The processing system may further submit the first modified voice input to the first service, obtain a first voice response from the first service, and present a voice output to the user in accordance with the first voice response.

Abstract: Content presentation is timed based on an individual's predicted mental state. In one example, a method performed by a processing system includes extracting a feature set from data that is collected by at least one sensor, where the sensor is monitoring an individual, the feature set comprises at least one feature of the individual, and the feature set excludes features extracted from images of the individual, predicting a current mental state of the individual, where the current mental state is predicted by providing the feature set as input to a machine learning model, sending media content to an endpoint device of the individual when the current mental state indicates that the individual is likely to be receptive to receiving the media content, and postponing sending media content to the endpoint device when the current mental state indicates that the individual is unlikely to be receptive to receiving the media content.

Abstract: Devices, computer-readable media, and methods for submitting a modified voice input to a service based upon a user intent determined from a voice input in accordance with a voice interface of the service are disclosed. A processing system including at least one processor may obtain a voice input of a user, determine an intent from the voice input, identify a first service, from among a plurality of services, in accordance with the intent, and formulate a first modified voice input from the voice input in accordance with a voice interface of the first service, where each of the services is associated with one of a plurality of different voice interfaces. The processing system may further submit the first modified voice input to the first service, obtain a first voice response from the first service, and present a voice output to the user in accordance with the first voice response.

Abstract: A system and method are disclosed for generating customized text-to-speech voices for a particular application. The method comprises generating a custom text-to-speech voice by selecting a voice for generating a custom text-to-speech voice associated with a domain, collecting text data associated with the domain from a pre-existing text data source and using the collected text data, generating an in-domain inventory of synthesis speech units by selecting speech units appropriate to the domain via a search of a pre-existing inventory of synthesis speech units, or by recording the minimal inventory for a selected level of synthesis quality. The text-to-speech custom voice for the domain is generated utilizing the in-domain inventory of synthesis speech units. Active learning techniques may also be employed to identify problem phrases wherein only a few minutes of recorded data is necessary to deliver a high quality TTS custom voice.