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    CENTRALIZED PREDICTIVE ROUTING USING DELAY PREDICTABILITY MEASUREMENTS
    1.
    发明申请
    CENTRALIZED PREDICTIVE ROUTING USING DELAY PREDICTABILITY MEASUREMENTS 有权
    使用延迟预测性测量的集中式预测路由

    公开(公告)号：US20150319076A1

    公开(公告)日：2015-11-05

    申请号：US14268500

    申请日：2014-05-02

    Applicant: Cisco Technology, Inc.

    Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Diane Bouchacourt

    IPC: H04L12/727 ,  H04L12/717 ,  H04L12/26 ,  H04L12/721

    CPC classification number: H04L45/121 ,  H04L43/0852 ,  H04L45/123 ,  H04L45/124 ,  H04L45/42

    Abstract: In one embodiment, a central device receives a routing strategy instruction that specifies a predictability threshold for communication delays in the network. The device estimates communication delays for a plurality of paths in the network and determines predictability measurements for the estimated delays. The device also selects, from among the plurality of paths, a particular path that has a predictability measurement that satisfies the predictability threshold and has a minimal estimated delay. The central device further installs the particular path at one or more other devices in the network.

    Abstract translation: 在一个实施例中，中央设备接收指定网络中的通信延迟的可预测性阈值的路由策略指令。 该设备估计网络中的多个路径的通信延迟并且确定估计的延迟的可预测性测量。 该装置还从多个路径中选择具有满足可预测性阈值并且具有最小估计延迟的可预测性测量的特定路径。 中央设备进一步将特定路径安装在网络中的一个或多个其他设备上。

    PROBING TECHNIQUE FOR PREDICTIVE ROUTING IN COMPUTER NETWORKS
    2.
    发明申请
    PROBING TECHNIQUE FOR PREDICTIVE ROUTING IN COMPUTER NETWORKS 有权
    在计算机网络中预测路由的探测技术

    公开(公告)号：US20150333997A1

    公开(公告)日：2015-11-19

    申请号：US14277411

    申请日：2014-05-14

    Applicant: Cisco Technology, Inc.

    Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Diane Bouchacourt

    IPC: H04L12/26

    CPC classification number: H04L43/12 ,  G06F13/00 ,  H04L41/142 ,  H04L41/147 ,  H04L43/04 ,  H04L43/067 ,  H04L43/0876 ,  H04L45/00 ,  H04L45/48

    Abstract: In one embodiment, network information associated with a plurality of nodes in a network is received at a device in a network. From the plurality of nodes, a node is selected based on a determination that the selected node is an outlier among the plurality of nodes according to the received network information. Then, a probe is sent to the selected node, and in response to the probe, a performance metric is received from the selected node at the device.

    Abstract translation: 在一个实施例中，在网络中的设备处接收与网络中的多个节点相关联的网络信息。 根据接收到的网络信息，从多个节点中选择节点，根据所选择的节点是多个节点之间的异常值的判定。 然后，探测器被发送到所选择的节点，并且响应于探测，从设备处的所选节点接收到性能度量。

    DISTRIBUTED PREDICTIVE ROUTING USING DELAY PREDICTABILITY MEASUREMENTS
    3.
    发明申请
    DISTRIBUTED PREDICTIVE ROUTING USING DELAY PREDICTABILITY MEASUREMENTS 有权
    使用延迟预测性测量的分布式预测路由

    公开(公告)号：US20150319077A1

    公开(公告)日：2015-11-05

    申请号：US14268627

    申请日：2014-05-02

    Applicant: Cisco Technology, Inc.

    Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Diane Bouchacourt

    IPC: H04L12/727 ,  H04L12/26 ,  H04L12/721

    CPC classification number: H04L45/124 ,  H04L43/0852 ,  H04L45/121 ,  H04L45/123 ,  H04L45/44

    Abstract: In one embodiment, a method is disclosed in which a device receives delay information for a communication segment in a network. The device determines a predictability measurement for delays along the segment using the received delay information. The predictability measurement is advertised to one or more devices in the network and used as a routing constraint to select a routing path in the network.

    Abstract translation: 在一个实施例中，公开了一种方法，其中设备接收网络中的通信段的延迟信息。 该设备使用接收到的延迟信息确定沿着该段的延迟的可预测性测量。 将可预测性测量通告给网络中的一个或多个设备，并用作路由约束来选择网络中的路由路径。

    Hierarchical hybrid batch-incremental learning
    5.
    发明授权
    Hierarchical hybrid batch-incremental learning 有权
    分层混合批量增量学习

    公开(公告)号：US09547828B2

    公开(公告)日：2017-01-17

    申请号：US14120371

    申请日：2014-05-14

    Applicant: Cisco Technology, Inc.

    Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Diane Bouchacourt

    IPC: G06F17/00 ,  G06N5/02 ,  G06N99/00 ,  G06N5/04 ,  H04L29/08 ,  H04L12/70 ,  H04L12/26 ,  H04L12/721 ,  H04L12/751

    CPC classification number: G06N99/005 ,  G06N5/048 ,  H04L41/147 ,  H04L41/16 ,  H04L43/08 ,  H04L45/02 ,  H04L45/70 ,  H04L47/00 ,  H04L67/10

    Abstract: In one embodiment, a machine learning model for predicting one or more metrics is run in a network which includes a centralized controller device interconnected with a plurality of edge devices. A batch version of the machine learning model that operates in batch mode is hosted at the centralized controller device. Then, an incremental version of the machine learning model that operates in incremental mode is pushed to an edge device of the plurality of edge devices, such that the incremental version of the machine learning model is hosted at the edge device. As a result, the batch version and the incremental version of the machine learning model run in parallel with one another.

    Abstract translation: 在一个实施例中，用于预测一个或多个度量的机器学习模型在包括与多个边缘设备互连的集中式控制器设备的网络中运行。 在批处理模式下运行的批量版本的机器学习模型托管在集中控制器设备上。 然后，以增量模式运行的机器学习模型的增量版本被推送到多个边缘设备的边缘设备，使得机器学习模型的增量版本被托管在边缘设备处。 因此，批量版本和机器学习模型的增量版本彼此并行运行。

    Distributed predictive routing using delay predictability measurements
    9.
    发明授权
    Distributed predictive routing using delay predictability measurements 有权
    使用延迟可预测性测量的分布式预测路由

    公开(公告)号：US09525617B2

    公开(公告)日：2016-12-20

    申请号：US14268627

    申请日：2014-05-02

    Applicant: Cisco Technology, Inc.

    Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Diane Bouchacourt

    IPC: H04L12/721 ,  H04L12/727 ,  H04L12/26

    CPC classification number: H04L45/124 ,  H04L43/0852 ,  H04L45/121 ,  H04L45/123 ,  H04L45/44

    Abstract: In one embodiment, a method is disclosed in which a device receives delay information for a communication segment in a network. The device determines a predictability measurement for delays along the segment using the received delay information. The predictability measurement is advertised to one or more devices in the network and used as a routing constraint to select a routing path in the network.

    Abstract translation: 在一个实施例中，公开了一种方法，其中设备接收网络中的通信段的延迟信息。 该设备使用接收到的延迟信息确定沿着该段的延迟的可预测性测量。 将可预测性测量通告给网络中的一个或多个设备，并用作路由约束来选择网络中的路由路径。

    Hierarchical hybrid batch-incremental learning
    10.
    发明申请
    Hierarchical hybrid batch-incremental learning 有权
    分层混合批量增量学习

    公开(公告)号：US20150332165A1

    公开(公告)日：2015-11-19

    申请号：US14120371

    申请日：2014-05-14

    Applicant: Cisco Technology, Inc.

    Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Diane Bouchacourt

    IPC: G06N99/00 ,  H04L29/08 ,  G06N5/04

    CPC classification number: G06N99/005 ,  G06N5/048 ,  H04L41/147 ,  H04L41/16 ,  H04L43/08 ,  H04L45/02 ,  H04L45/70 ,  H04L47/00 ,  H04L67/10

    Abstract: In one embodiment, a machine learning model for predicting one or more metrics is run in a network which includes a centralized controller device interconnected with a plurality of edge devices. A batch version of the machine learning model that operates in batch mode is hosted at the centralized controller device. Then, an incremental version of the machine learning model that operates in incremental mode is pushed to an edge device of the plurality of edge devices, such that the incremental version of the machine learning model is hosted at the edge device. As a result, the batch version and the incremental version of the machine learning model run in parallel with one another.

    Abstract translation: 在一个实施例中，用于预测一个或多个度量的机器学习模型在包括与多个边缘设备互连的集中式控制器设备的网络中运行。 在批处理模式下运行的批量版本的机器学习模型托管在集中控制器设备上。 然后，以增量模式运行的机器学习模型的增量版本被推送到多个边缘设备的边缘设备，使得机器学习模型的增量版本被托管在边缘设备处。 因此，批量版本和机器学习模型的增量版本彼此并行运行。

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