LINK BEHAVIOR PREDICTION FOR USE IN PATH SELECTION

    公开(公告)号:US20230412488A1

    公开(公告)日:2023-12-21

    申请号:US17808066

    申请日:2022-06-21

    CPC classification number: H04L45/123 H04L45/124 H04L45/08

    Abstract: Techniques are described for predicting future behavior of links in a network and generating dynamic thresholds for link metrics for use in path selection. In one example, a computing system receives historical values of a link metric for links of a network. The computing system executes a machine learning system which processes the historical values of the link metric to generate: (1) a predicted future value of the link metric for each link; and (2) a threshold for the link metric indicating whether the predicted future value for each link is anomalous. The computing system computes a path based on the predicted future values of the link metric and the threshold for the link metric. The computing system provisions the computed path, thereby enabling a network device to forward network traffic along the computed path.

    Link behavior prediction for use in path selection

    公开(公告)号:US12170608B2

    公开(公告)日:2024-12-17

    申请号:US17808066

    申请日:2022-06-21

    Abstract: Techniques are described for predicting future behavior of links in a network and generating dynamic thresholds for link metrics for use in path selection. In one example, a computing system receives historical values of a link metric for links of a network. The computing system executes a machine learning system which processes the historical values of the link metric to generate: (1) a predicted future value of the link metric for each link; and (2) a threshold for the link metric indicating whether the predicted future value for each link is anomalous. The computing system computes a path based on the predicted future values of the link metric and the threshold for the link metric. The computing system provisions the computed path, thereby enabling a network device to forward network traffic along the computed path.

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