Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: Concepts and technologies are disclosed herein for a virtualized services discovery and recommendation engine. A request for a service can be received from a requestor. The request can include feature data that can define two or more features. Two or more features can be determined based on the feature data and requestor data associated with the requestor can be obtained. Two or more services that satisfy the request can be identified and a recommendation that represents the two or more services can be generated. The recommendation can include a data representation of a custom product that can include the two or more services. The recommendation can be tested to determine if the custom product functions, and the recommendation can be provided to the requestor.

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: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: System and computer-implemented method for license management of virtual appliances in a computing system uses an activated virtual appliance in the computing system to forward an activation license from a license server on behalf of an unactivated virtual appliance in the computing system.

Abstract: Concepts and technologies disclosed herein are directed to systems, methods, and computer-readable storage media for designing, creating, and deploying composite machine learning applications in cloud environments. According to one aspect disclosed herein, a system, including a processor and memory, can present a design studio canvas upon which a user can design a composite machine learning application from at least one of a plurality of building blocks stored in a design studio catalog. The system can receive input to design, on the design studio canvas, a visual representation of the composite machine learning application. The system can save the visual representation of the composite machine learning application, and, in response to saving the visual representation of the composite machine learning application, can generate a composition dump file that includes a graph structure of the composite machine learning application.

Abstract: An automated and model driven mini-cloud deployment method comprising: instantiating a model driven orchestrator; parsing a blueprint to develop a virtual network function topology including: identifying infrastructure components required to establish at least one virtual network function; identifying at least one dependency for the at least one virtual network function; providing a sequence for calling life cycle operations; the model driven orchestrator effectuates the life cycle operations comprising: establishing a uCPE as a tenant within a network registry, configuring the uCPE, and activating the uCPE; and instantiating the at least one virtual network function on the uCPE according to the virtual network function topology.

Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

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: An automated and model driven mini-cloud deployment method comprising: instantiating a model driven orchestrator; parsing a blueprint to develop a virtual network function topology including: identifying infrastructure components required to establish at least one virtual network function; identifying at least one dependency for the at least one virtual network function; providing a sequence for calling life cycle operations; the model driven orchestrator effectuates the life cycle operations comprising: establishing a uCPE as a tenant within a network registry, configuring the uCPE, and activating the uCPE; and instantiating the at least one virtual network function on the uCPE according to the virtual network function topology.

Abstract: Concepts and technologies are disclosed herein for a virtualized services discovery and recommendation engine. A request for a service can be received from a requestor. The request can include feature data that can define two or more features. Two or more features can be determined based on the feature data and requestor data associated with the requestor can be obtained. Two or more services that satisfy the request can be identified and a recommendation that represents the two or more services can be generated. The recommendation can include a data representation of a custom product that can include the two or more services. The recommendation can be tested to determine if the custom product functions, and the recommendation can be provided to the requestor.

Abstract: Concepts and technologies are disclosed herein for a virtualized services discovery and recommendation engine. A request for a service can be received from a requestor. The request can include feature data that can define two or more features. Two or more features can be determined based on the feature data and requestor data associated with the requestor can be obtained. Two or more services that satisfy the request can be identified and a recommendation that represents the two or more services can be generated. The recommendation can include a data representation of a custom product that can include the two or more services. The recommendation can be tested to determine if the custom product functions, and the recommendation can be provided to the requestor.

Abstract: Methods, non-transitory computer readable media, and devices are disclosed for rendering a visualization using a package to expand a statistical programming language. For example, a processor may load the package, which may comprise a plurality of application programming interfaces including a first application programming interface for generating a first object to contain a metadata set and a second application programming interface for generating a second object for rendering a visual output to present via a display. In one example, the metadata set includes content data and information regarding a formatting of at least one visualization based on the content data. The processor may further configure the first object via the first application programming interface, configure the second object via the second application programming interface, and render the visual output via the second object, the visual output including the at least one visualization.

Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: A method, computer readable medium for diagnosing wireless network performance via a customer endpoint device are disclosed. For example, the method receives a request to perform a wireless network performance diagnostic test that is initiated by a customer endpoint device, establishes a session with the customer endpoint device, performs the wireless network performance diagnostic test in response to the request via the session using a packet generated by the customer endpoint device and provides diagnostic test data gathered from the wireless network performance diagnostic test to the customer endpoint device.

Abstract: A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

Abstract: Methods, non-transitory computer readable media, and devices are disclosed for rendering a visualization using a package to expand a statistical programming language. For example, a processor may load the package, which may comprise a plurality of application programming interfaces including a first application programming interface for generating a first object to contain a metadata set and a second application programming interface for generating a second object for rendering a visual output to present via a display. In one example, the metadata set includes content data and information regarding a formatting of at least one visualization based on the content data. The processor may further configure the first object via the first application programming interface, configure the second object via the second application programming interface, and render the visual output via the second object, the visual output including the at least one visualization.

Abstract: A model-driven system automatically deploys a virtualized service, including multiple service components, on a distributed cloud infrastructure. A master service orchestrator causes a cloud platform orchestrator to retrieve a cloud services archive file, extract a cloud resource configuration template and create cloud resources at appropriate data centers as specified. The master service orchestrator also causes a software defined network controller to retrieve the cloud services archive file, to extract a cloud network configuration template and to configure layer 1 through layer 3 virtual network functions and to set up routes between them. Additionally, the master service orchestrator causes an application controller to retrieve the cloud services archive file, to extract a deployment orchestration plan and to configure and start layer 4 through layer 7 application components and bring them to a state of operational readiness.