ACCESS POINT COORDINATION USING GRAPHS AND MACHINE LEARNING PROCESSES

    公开(公告)号:US20240267748A1

    公开(公告)日:2024-08-08

    申请号:US18166264

    申请日:2023-02-08

    CPC classification number: H04W16/20 H04L41/16 H04W84/12

    Abstract: AP coordination, and more specifically intelligent AP coordination using a graph network and reinforcement learning may be provided. AP coordination may include translating a physical space into a logical space, wherein the physical space is being evaluated for AP coordination. A machine learning process may predict signal strengths of signals sent by one or more Access Points (APs) and received by one or more Stations (STAs), wherein the machine learning process uses the logical space, and wherein each STA is in a location of the physical space. One or more AP placements may be evaluated based on the signal strengths, and a recommended AP placement may be determined based on the evaluation.

    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK

    公开(公告)号:US20240135279A1

    公开(公告)日:2024-04-25

    申请号:US17973121

    申请日:2022-10-24

    CPC classification number: G06Q10/063118

    Abstract: Methods are provided in which a computing device obtains user data and network data associated with one or more assets used in an enterprise network of a user. The computing device further determines an identity of the user based on the user data and the network data and generates a task recommendation based on the identity of the user. The task recommendation includes one or more tasks having a plurality of operations that are to be performed within a predetermined time interval. The computing device further provides the task recommendation for performing one or more actions associated with configuring the enterprise network.

    HIERARCHICAL PARTNER RISK EVALUATION USING FUZZY LOGIC

    公开(公告)号:US20250037056A1

    公开(公告)日:2025-01-30

    申请号:US18359409

    申请日:2023-07-26

    Abstract: Methods are provided which involve obtaining enterprise data about a plurality of assets and configuration of an enterprise network, and partner data about one or more network related partner services for the enterprise network. The methods further involve determining one or more hierarchical relationships among the plurality of assets, the enterprise network, and the one or more network related partner services, by performing machine learning on the enterprise data and the partner data. Additionally, the methods involve generating one or more risk values based on the one or more hierarchical relationships and providing the one or more risk values indicative of performance of the one or more network related partner services.

    HIERARCHICAL AUTO SUMMARY GENERATION WITH MULTI-TASK LEARNING IN NETWORKING RECOMMENDATIONS

    公开(公告)号:US20240314020A1

    公开(公告)日:2024-09-19

    申请号:US18184972

    申请日:2023-03-16

    CPC classification number: H04L41/065 H04L41/069 H04L41/16

    Abstract: Methods are provided for generating hierarchical summaries with actionable recommendations having various granularities. Specifically, the methods involve obtaining notifications related to network issues and generating meta-semantic data that includes a summary of each of the notifications. The methods further involve obtaining inventory data of network devices in a plurality of domains of a network. The inventory data includes configuration information of the network devices. The methods further involve generating a multi-level hierarchical summary specific to the network based on the inventory data and the meta-semantic data. The multi-level hierarchical summary includes a first level specific to one or more affected network devices and a second level specific to a group of network devices. The methods further involve providing the multi-level hierarchical summary for performing one or more actions associated with the network.

    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK

    公开(公告)号:US20240232747A9

    公开(公告)日:2024-07-11

    申请号:US17973121

    申请日:2022-10-25

    CPC classification number: G06Q10/063118

    Abstract: Methods are provided in which a computing device obtains user data and network data associated with one or more assets used in an enterprise network of a user. The computing device further determines an identity of the user based on the user data and the network data and generates a task recommendation based on the identity of the user. The task recommendation includes one or more tasks having a plurality of operations that are to be performed within a predetermined time interval. The computing device further provides the task recommendation for performing one or more actions associated with configuring the enterprise network.

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