LOCATION-BASED SERVICE NETWORK AUTOMATION PLATFORM

    公开(公告)号:US20250039697A1

    公开(公告)日:2025-01-30

    申请号:US18911375

    申请日:2024-10-10

    Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving network configuration data from a plurality of location-based services nodes in a network; transforming the network configuration data into reference audit values; comparing the reference audit values with the network configuration data received from each location-based services node in the plurality of location-based services nodes to generate corrections; and sending the corrections to each location-based services node in the plurality of location-based services nodes responsive to the network configuration data deviating from the reference audit values. Other embodiments are disclosed.

    SYNCHRONIZATION OF ARTIFICIAL INTELLIGENCE BASED MICROSERVICES

    公开(公告)号:US20250016887A1

    公开(公告)日:2025-01-09

    申请号:US18886432

    申请日:2024-09-16

    Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.

    LOCATION-BASED SERVICE NETWORK AUTOMATION PLATFORM

    公开(公告)号:US20230370866A1

    公开(公告)日:2023-11-16

    申请号:US17742521

    申请日:2022-05-12

    CPC classification number: H04W24/02 H04W4/025 H04L41/0823 H04W88/16

    Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving network configuration data from a plurality of location-based services nodes in a network; transforming the network configuration data into reference audit values; comparing the reference audit values with the network configuration data received from each location-based services node in the plurality of location-based services nodes to generate corrections; and sending the corrections to each location-based services node in the plurality of location-based services nodes responsive to the network configuration data deviating from the reference audit values. Other embodiments are disclosed.

    SYNCHRONIZATION OF ARTIFICIAL INTELLIGENCE BASED MICROSERVICES

    公开(公告)号:US20220272794A1

    公开(公告)日:2022-08-25

    申请号:US17182418

    申请日:2021-02-23

    Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.

    MODEL DRIVEN PROCESS FOR AUTOMATED DEPLOYMENT OF DOMAIN 2.0 VIRTUALIZED SERVICES AND APPLICATIONS ON CLOUD INFRASTRUCTURE

    公开(公告)号:US20220086055A1

    公开(公告)日:2022-03-17

    申请号:US17537741

    申请日:2021-11-30

    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.

    Virtualized services discovery and recommendation engine

    公开(公告)号:US11138645B2

    公开(公告)日:2021-10-05

    申请号:US16186892

    申请日:2018-11-12

    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.

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