MACHINE LEARNING BASED NETWORK DRIVE TEST PRIORITIZATION

    公开(公告)号:US20250133427A1

    公开(公告)日:2025-04-24

    申请号:US18489800

    申请日:2023-10-18

    Abstract: Technologies for network drive test prioritization based on machine learning are disclosed. An example method includes feeding a representation of routes of a target candidate drive test to a trained machine learning model to obtain a drive test prediction, wherein the trained machine learning model is trained based on integrating radio frequency (RF) estimations or predictions with past drive test data. The method also includes sorting a set of candidate drive tests for the communications network including the target candidate drive test, based on drive test predictions associated with each candidate drive test, to determine priorities for executing drive tests; and determining expectation of network usability in accordance with network availability and performance metrics.

    MANAGEMENT OF APPLICATION PROGRAMMING INTERFACES FOR MICROSERVICES OF NETWORK FUNCTIONS

    公开(公告)号:US20250071022A1

    公开(公告)日:2025-02-27

    申请号:US18455497

    申请日:2023-08-24

    Abstract: Technologies for facilitating APIs for microservices associated with a communications network are disclosed. An example method includes receiving a request to a target API exposed by an API platform, and invoking a combination of API governance modules corresponding to the target API and selected from API governance modules implemented remotely from the API platform, to map the request to microservices. The microservices include internal microservice(s) maintained within the communications network and external microservice(s) maintained externally to the communications network. The method also includes applying API governance policies indicated by the combination of API governance modules to validate interactions with the external microservice(s) based on the request and generating and sending a response to the request.

Patent Agency Ranking