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    AI-ASSISTED WAN LINK SELECTION FOR SD-WAN SERVICES
    2.
    发明公开
    AI-ASSISTED WAN LINK SELECTION FOR SD-WAN SERVICES 审中-公开

    公开(公告)号：US20240250910A1

    公开(公告)日：2024-07-25

    申请号：US18628122

    申请日：2024-04-05

    Applicant: Juniper Networks, Inc.

    Inventor： Jisheng Wang ,  Michael Baj ,  Patrick Timmons ,  Patrick J. MeLampy ,  Kaushik Adesh Agrawal ,  Ruchit Rajkumar Mehta

    IPC: H04L47/2425

    CPC classification number: H04L47/2425

    Abstract: An example method includes receiving, by a software-defined networking in a wide area network (SD-WAN) system having a first WAN link and a second WAN link for an SD-WAN service, WAN link characterization data for the first WAN link over a time period; determining, by the SD-WAN system based on processing the WAN link characterization data for the first WAN link using a machine learning model trained with historical WAN link characterization data for one or more WAN links, an indicator of a predicted performance metric of the first WAN link at a future time; and reassigning, by the SD-WAN system based on the indicator, an application from the first WAN link to the second WAN link.

    NETWORK POLICY APPLICATION BASED ON SESSION STATE
    6.
    发明申请
    NETWORK POLICY APPLICATION BASED ON SESSION STATE 有权

    公开(公告)号：US20220200915A1

    公开(公告)日：2022-06-23

    申请号：US17454071

    申请日：2021-11-09

    Applicant: Juniper Networks, Inc.

    Inventor： Patrick Timmons

    IPC: H04L12/859 ,  H04L29/08

    Abstract: Techniques are disclosed for the detection of different states of a session comprising a bidirectional flow of network traffic between client devices so as to enable a network device to apply different network policies to different states of the session. In one example, a computing device identifies multiple states of a session and defines a plurality of network policies. Each network policy defines performance requirements for network traffic during each state of the session. A network device receives the plurality of network policies and determines a state of the session. The network device selects a path based on the performance requirements of the network policy associated with the determined state of the session. The network device forwards traffic associated with the session along the selected path while the session is in the determined state.

    Logical path down scope analysis
    7.
    发明授权
    Logical path down scope analysis 有权

    公开(公告)号：US12289220B1

    公开(公告)日：2025-04-29

    申请号：US18063591

    申请日：2022-12-08

    Applicant: Juniper Networks, Inc.

    Inventor： Amit Pillay ,  Xiaoying Wu ,  Patrick Timmons

    IPC: H04L43/062 ,  H04L41/0631

    Abstract: A network management system (NMS) generates a hierarchical attribution graph representing different scopes at different hierarchical levels of a wide area network (WAN); obtains logical path down data indicative of operational behavior including failure events associated with logical paths of network devices over the WAN; obtains total path data indicative of a historical number of active logical paths between the network devices; and determines a scope of a logical path down issue by, for a time period of the logical path down issue, determining a score for each scope of the different scopes based on the logical path down data aggregated across the respective scope and the total path data, and determining the scope of the logical path down issue as a particular scope of the different scopes having a highest score. The NMS may identify the particular scope as a root cause of the logical path down issue.

    AI-assisted WAN link selection for SD-WAN services
    8.
    发明授权
    AI-assisted WAN link selection for SD-WAN services 有权

    公开(公告)号：US11991084B2

    公开(公告)日：2024-05-21

    申请号：US17491265

    申请日：2021-09-30

    Applicant: Juniper Networks, Inc.

    Inventor： Jisheng Wang ,  Michael Baj ,  Patrick Timmons ,  Patrick J. MeLampy ,  Kaushik Adesh Agrawal ,  Ruchit Rajkumar Mehta

    IPC: H04L47/2425

    CPC classification number: H04L47/2425

    Abstract: An example method includes receiving, by a software-defined networking in a wide area network (SD-WAN) system having a first WAN link and a second WAN link for an SD-WAN service, WAN link characterization data for the first WAN link over a time period; determining, by the SD-WAN system based on processing the WAN link characterization data for the first WAN link using a machine learning model trained with historical WAN link characterization data for one or more WAN links, an indicator of a predicted performance metric of the first WAN link at a future time; and reassigning, by the SD-WAN system based on the indicator, an application from the first WAN link to the second WAN link.

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