DETECTING NETWORK EVENTS HAVING ADVERSE USER IMPACT

    公开(公告)号:US20240291743A1

    公开(公告)日:2024-08-29

    申请号:US18656206

    申请日:2024-05-06

    CPC classification number: H04L43/0876 H04L41/0631 H04L43/062 H04L45/48

    Abstract: A method includes receiving, by a network management system, network data from a plurality of network devices configured to provide a network at a site; receiving, by the processing circuitry, user impact data from a plurality of client devices that access the network at the site; determining, based on the network data, a pattern of one or more network events occurring over time; correlating in time the pattern of the one or more network events to an adverse user impact event indicated by the user impact data received from the plurality of client devices; and determining, in response to the correlating, an instance of overwhelming network traffic having an adverse user impact. In some examples, the network data includes network traffic impact data, such as a number of packets dropped at a switch port due to congestion.

    Identifying root cause of failures through detection of network scope failures

    公开(公告)号:US11838172B2

    公开(公告)日:2023-12-05

    申请号:US17446601

    申请日:2021-08-31

    CPC classification number: H04L41/0631 H04W24/04

    Abstract: Techniques are described by which a network management system (NMS) is configured to provide identification of root cause failure through the detection of network scope failures. For example, the NMS comprises one or more processors; and a memory comprising instructions that when executed by the one or more processors cause the one or more processors to: generate a hierarchical attribution graph comprising attributes representing different network scopes at different hierarchical levels; receive network event data, wherein the network event data is indicative of operational behavior of the network, including one or more of successful events or one or more failure events associated with one or more client devices; and apply a machine learning model to the network event data and to a particular network scope in the hierarchical attribution graph to detect whether the particular network scope has failure.

    Identifying root cause of failures through detection of network scope failures

    公开(公告)号:US12301403B2

    公开(公告)日:2025-05-13

    申请号:US18527471

    申请日:2023-12-04

    Abstract: Techniques are described by which a network management system (NMS) is configured to provide identification of root cause failure through the detection of network scope failures. For example, the NMS comprises one or more processors; and a memory comprising instructions that when executed by the one or more processors cause the one or more processors to: generate a hierarchical attribution graph comprising attributes representing different network scopes at different hierarchical levels; receive network event data, wherein the network event data is indicative of operational behavior of the network, including one or more of successful events or one or more failure events associated with one or more client devices; and apply a machine learning model to the network event data and to a particular network scope in the hierarchical attribution graph to detect whether the particular network scope has failure.

    DETECTING WIRED CLIENT STUCK
    4.
    发明公开

    公开(公告)号:US20240223434A1

    公开(公告)日:2024-07-04

    申请号:US18148232

    申请日:2022-12-29

    CPC classification number: H04L41/0604 H04L41/142 H04L41/16

    Abstract: Techniques are described for detecting that a client device physically connected to a network device is “stuck,” that is, the client device is not sending or receiving network packets with the network device. A network management system (NMS) receives current network statistics of ports of network devices with respect to client devices physically connected to the ports. The NMS identifies a candidate client device connected to a particular port of a particular network device for which the current network statistics indicate an issue. The NMS detects anomalous behavior of the candidate client device based on one or more features of the current network statistics, historical baseline statistics associated with the candidate client device, and peer statistics associated with one or more peer client devices of a same device type as the candidate client device. The NMS outputs a notification of the anomalous behavior.

    DETECTING NETWORK EVENTS HAVING ADVERSE USER IMPACT

    公开(公告)号:US20230308374A1

    公开(公告)日:2023-09-28

    申请号:US17812676

    申请日:2022-07-14

    CPC classification number: H04L43/0876 H04L41/0631 H04L45/48 H04L43/062

    Abstract: A method includes receiving, by a network management system, network data from a plurality of network devices configured to provide a network at a site; receiving, by the processing circuitry, user impact data from a plurality of client devices that access the network at the site; determining, based on the network data, a pattern of one or more network events occurring over time; correlating in time the pattern of the one or more network events to an adverse user impact event indicated by the user impact data received from the plurality of client devices; and determining, in response to the correlating, an instance of overwhelming network traffic having an adverse user impact. In some examples, the network data includes network traffic impact data, such as a number of packets dropped at a switch port due to congestion.

    IDENTIFYING ROOT CAUSE OF FAILURES THROUGH DETECTION OF NETWORK SCOPE FAILURES

    公开(公告)号:US20240097969A1

    公开(公告)日:2024-03-21

    申请号:US18527471

    申请日:2023-12-04

    CPC classification number: H04L41/0631 H04W24/04

    Abstract: Techniques are described by which a network management system (NMS) is configured to provide identification of root cause failure through the detection of network scope failures. For example, the NMS comprises one or more processors; and a memory comprising instructions that when executed by the one or more processors cause the one or more processors to: generate a hierarchical attribution graph comprising attributes representing different network scopes at different hierarchical levels; receive network event data, wherein the network event data is indicative of operational behavior of the network, including one or more of successful events or one or more failure events associated with one or more client devices; and apply a machine learning model to the network event data and to a particular network scope in the hierarchical attribution graph to detect whether the particular network scope has failure.

    Detecting network events having adverse user impact

    公开(公告)号:US12021722B2

    公开(公告)日:2024-06-25

    申请号:US17812676

    申请日:2022-07-14

    CPC classification number: H04L43/0876 H04L41/0631 H04L43/062 H04L45/48

    Abstract: A method includes receiving, by a network management system, network data from a plurality of network devices configured to provide a network at a site; receiving, by the processing circuitry, user impact data from a plurality of client devices that access the network at the site; determining, based on the network data, a pattern of one or more network events occurring over time; correlating in time the pattern of the one or more network events to an adverse user impact event indicated by the user impact data received from the plurality of client devices; and determining, in response to the correlating, an instance of overwhelming network traffic having an adverse user impact. In some examples, the network data includes network traffic impact data, such as a number of packets dropped at a switch port due to congestion.

    IDENTIFYING ROOT CAUSE OF FAILURES THROUGH DETECTION OF NETWORK SCOPE FAILURES

    公开(公告)号:US20230069434A1

    公开(公告)日:2023-03-02

    申请号:US17446601

    申请日:2021-08-31

    Abstract: Techniques are described by which a network management system (NMS) is configured to provide identification of root cause failure through the detection of network scope failures. For example, the NMS comprises one or more processors; and a memory comprising instructions that when executed by the one or more processors cause the one or more processors to: generate a hierarchical attribution graph comprising attributes representing different network scopes at different hierarchical levels; receive network event data, wherein the network event data is indicative of operational behavior of the network, including one or more of successful events or one or more failure events associated with one or more client devices; and apply a machine learning model to the network event data and to a particular network scope in the hierarchical attribution graph to detect whether the particular network scope has failure.

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