EVENTS DATA STRUCTURE FOR REAL TIME NETWORK DIAGNOSIS

    公开(公告)号:US20220245049A1

    公开(公告)日:2022-08-04

    申请号:US17726128

    申请日:2022-04-21

    摘要: Aspects of the subject disclosure may include, for example, a method that includes detecting events relating to user equipment on a communication network, collecting first event data including event times and locations, and collecting second event data regarding second event dimensions determined at least in part by the event type. The method also includes generating, for each of the event types, an event data structure associated with the user, based on the first event data and second event data. The event data structures are concatenated to generate an event history flow associated with the user; the event history flow is analyzed to identify causal events for a detected event. The method also includes generating a model for performance of the user equipment based on the causal events to predict a future event, and identifying potential adjustments to the communication network to prevent that event. Other embodiments are disclosed.

    EVENTS DATA STRUCTURE FOR REAL TIME NETWORK DIAGNOSIS

    公开(公告)号:US20210124671A1

    公开(公告)日:2021-04-29

    申请号:US17143835

    申请日:2021-01-07

    摘要: Aspects of the subject disclosure may include, for example, a method that includes detecting events relating to user equipment on a communication network, collecting first event data including event times and locations, and collecting second event data regarding second event dimensions determined at least in part by the event type. The method also includes generating, for each of the event types, an event data structure associated with the user, based on the first event data and second event data. The event data structures are concatenated to generate an event history flow associated with the user; the event history flow is analyzed to identify causal events for a detected event. The method also includes generating a model for performance of the user equipment based on the causal events to predict a future event, and identifying potential adjustments to the communication network to prevent that event. Other embodiments are disclosed.