LEARNING MACHINE-BASED GRANULAR SEGMENT/PATH CHARACTERISTIC PROBING TECHNIQUE
    151.
    发明申请
    LEARNING MACHINE-BASED GRANULAR SEGMENT/PATH CHARACTERISTIC PROBING TECHNIQUE 有权
    基于机器的颗粒分段/路径特征探测技术

    公开(公告)号:US20150195184A1

    公开(公告)日:2015-07-09

    申请号:US14164544

    申请日:2014-01-27

    Abstract: In one embodiment, a routing topology of a network including nodes interconnected by communication links is determined. Important nodes in the network which are of relative importance are determined based on their location in the determined routing topology. Also, one or more request messages are sent causing the important nodes to gather local network metrics. Then, in response to the one or more request messages, one or more response messages including the network metrics gathered by each important node are received.

    Abstract translation: 在一个实施例中,确定包括由通信链路互连的节点的网络的路由拓扑。 基于其在确定的路由拓扑中的位置来确定网络中具有相对重要性的重要节点。 此外,发送一个或多个请求消息,导致重要节点收集本地网络度量。 然后,响应于一个或多个请求消息,接收包括由每个重要节点收集的网络度量的一个或多个响应消息。

    DISTRIBUTED AND LEARNING MACHINE-BASED APPROACH TO GATHERING LOCALIZED NETWORK DYNAMICS
    152.
    发明申请
    DISTRIBUTED AND LEARNING MACHINE-BASED APPROACH TO GATHERING LOCALIZED NETWORK DYNAMICS 有权
    基于分布式和学习机器的方法来实现本地化网络动态

    公开(公告)号:US20150195144A1

    公开(公告)日:2015-07-09

    申请号:US14164444

    申请日:2014-01-27

    Abstract: In one embodiment, one or more reporting nodes are selected to report network metrics in a network. From a monitoring node in the network, a trigger message is sent to the one or more reporting nodes. The trigger message may trigger the one or more reporting nodes to report one or more network metrics local to the respective reporting node. In response to the trigger message, a report of the one or more network metrics is received at the monitoring node from one of the one or more reporting nodes.

    Abstract translation: 在一个实施例中,选择一个或多个报告节点来报告网络中的网络度量。 从网络中的监视节点,触发消息被发送到一个或多个报告节点。 触发消息可以触发一个或多个报告节点向本地报告节点报告一个或多个网络度量。 响应于触发消息,在监视节点从一个或多个报告节点之一接收一个或多个网络度量的报告。

    REDUCED AUTHENTICATION TIMES IN CONSTRAINED COMPUTER NETWORKS
    155.
    发明申请
    REDUCED AUTHENTICATION TIMES IN CONSTRAINED COMPUTER NETWORKS 审中-公开
    约束计算机网络中的减少认证时间

    公开(公告)号:US20150156199A1

    公开(公告)日:2015-06-04

    申请号:US14616223

    申请日:2015-02-06

    Abstract: In one embodiment, a capable node in a low power and lossy network (LLN) may monitor the authentication time for one or more nodes in the LLN. The capable node may dynamically correlate the authentication time with the location of the one or more nodes in the LLN in order to identify one or more authentication-delayed nodes. The node may then select, based on the location of the one or more authentication-delayed nodes, one or more key-delegation nodes to receive one or more network keys so that the key-delegation nodes may perform localized authentication of one or more of the authentication-delayed nodes. The capable node may then distribute the one or more network keys to the one or more key-delegation nodes.

    Abstract translation: 在一个实施例中,低功率和有损网络(LLN)中的能力节点可以监视LLN中的一个或多个节点的认证时间。 能力节点可以将认证时间与LLN中的一个或多个节点的位置动态相关,以便识别一个或多个认证延迟节点。 然后,节点可以基于一个或多个认证延迟的节点的位置来选择一个或多个密钥委派节点来接收一个或多个网络密钥,使得密钥委派节点可以执行一个或多个 认证延迟节点。 有能力的节点可以然后将一个或多个网络密钥分配给一个或多个密钥委派节点。

    USING STATISTICAL AND HISTORICAL INFORMATION OF TOPOLOGY METRICS IN CONSTRAINED NETWORKS
    156.
    发明申请
    USING STATISTICAL AND HISTORICAL INFORMATION OF TOPOLOGY METRICS IN CONSTRAINED NETWORKS 有权
    在约束网络中使用拓扑学量度的统计和历史信息

    公开(公告)号:US20150023174A1

    公开(公告)日:2015-01-22

    申请号:US13947268

    申请日:2013-07-22

    Abstract: Statistical and historical values of performance metrics are actively used to influence routing decisions for optimum topologies in a constrained network. Traffic service level is constantly monitored and compared with a service level agreement. If deviation exists between the monitored traffic service level and the terms of the service level agreement, stability metrics are used to maintain paths through the network that meet the terms of the traffic service level agreement or that improve the traffic flow through the network. Backup parent selection for a node in the network is performed based on previous performance of backup parents for the node.

    Abstract translation: 绩效指标的统计和历史价值被积极地用于影响约束网络中最优拓扑的路由决策。 不断监控流量服务水平,并与服务水平协议进行比较。 如果监控的流量服务级别与服务级别协议的条款之间存在偏差,则使用稳定性度量来维护通过网络的路径,以满足流量服务级别协议的条件或改善通过网络的流量。 基于节点的备份父节点的先前性能,执行网络中节点的备份父选择。

    AGGREGATED DELIVERY OF TUNNEL FAULT MESSAGES ON COMMON ETHERNET SEGMENTS
    157.
    发明申请
    AGGREGATED DELIVERY OF TUNNEL FAULT MESSAGES ON COMMON ETHERNET SEGMENTS 有权
    在共同以太网部分集体提供隧道故障消息

    公开(公告)号:US20150006946A1

    公开(公告)日:2015-01-01

    申请号:US13928852

    申请日:2013-06-27

    CPC classification number: H04L41/0686 H04L45/28 H04L45/50

    Abstract: In one embodiment, a device in a computer network determines one or more tunnels affected by a downstream fault in the computer network, and determines one or more common Ethernet segments of the device used by the affected tunnels. As such, the device generates, for each of the one or more common Ethernet segments, a respective fault message aggregating tunnel information of each of one or more particular affected tunnels on the corresponding common Ethernet segment, and sends each respective fault message with aggregated tunnel information over a selected tunnel of the one or more particular affected tunnels on the corresponding common Ethernet segment.

    Abstract translation: 在一个实施例中,计算机网络中的设备确定受计算机网络中的下游故障影响的一个或多个隧道,并确定受影响隧道使用的设备的一个或多个公共以太网段。 因此,该设备为一个或多个公共以太网段中的每一个生成相应的故障消息,聚​​合对应的公共以太网段上的一个或多个特定受影响隧道中的每一个的隧道信息,并且将每个相应的故障消息发送到聚合隧道 通过相应公共以太网段上的一个或多个特定受影响隧道的选定隧道的信息。

    CUMULATIVE NODE HEARTBEAT RELAY AGENTS IN CONSTRAINED COMPUTER NETWORKS
    158.
    发明申请
    CUMULATIVE NODE HEARTBEAT RELAY AGENTS IN CONSTRAINED COMPUTER NETWORKS 有权
    计算机网络中的累积节点心脏继电器

    公开(公告)号:US20140379900A1

    公开(公告)日:2014-12-25

    申请号:US13926761

    申请日:2013-06-25

    CPC classification number: H04L41/145 H04L43/0805 H04L43/10 Y04S40/168

    Abstract: In one embodiment, a message instructing a particular node to act as a heartbeat relay agent is received at the particular node in a network. The particular node is selected to receive the message based on a centrality of the particular node. Heartbeat messages are then collected from child nodes of the particular node in the network. Based on the collected heartbeat messages, a heartbeat report is generated, and the report is transmitted to a collecting node in the network.

    Abstract translation: 在一个实施例中,指示特定节点充当心跳中继代理的消息在网络中的特定节点处被接收。 选择特定节点以基于特定节点的中心性接收消息。 然后从网络中的特定节点的子节点收集心跳消息。 基于收集到的心跳消息,生成心跳报告,并将报告发送到网络中的收集节点。

    DYNAMICALLY DETERMINING NODE LOCATIONS TO APPLY LEARNING MACHINE BASED NETWORK PERFORMANCE IMPROVEMENT
    159.
    发明申请
    DYNAMICALLY DETERMINING NODE LOCATIONS TO APPLY LEARNING MACHINE BASED NETWORK PERFORMANCE IMPROVEMENT 有权
    动态确定节点位置以应用基于机器的网络性能改进

    公开(公告)号:US20140222983A1

    公开(公告)日:2014-08-07

    申请号:US13946227

    申请日:2013-07-19

    CPC classification number: H04L41/16 H04L41/0677 H04L41/12 H04L43/10

    Abstract: In one embodiment, techniques are shown and described relating to dynamically determining node locations to apply learning machine based network performance improvement. In particular, a degree of significance of nodes in a network, respectively, is calculated based on one or more significance factors. One or more significant nodes are then determined based on the calculated degree of significance. Additionally, a nodal region in the network of deteriorated network health is determined, and the nodal region of deteriorated network health is correlated with a significant node of the one or more significant nodes.

    Abstract translation: 在一个实施例中,显示和描述与动态确定节点位置以应用基于学习机的网络性能改进相关的技术。 特别地,基于一个或多个重要因素来分别计算网络中节点的重要程度。 然后基于所计算的显着程度来确定一个或多个有效节点。 另外,确定网络健康状况恶化的网络中的节点区域,将网络运行恶化的节点区域与一个或多个重要节点的重要节点相关联。

    DISTRIBUTED ARCHITECTURE FOR LAYERED HIDDEN MARKOV MODELS
    160.
    发明申请
    DISTRIBUTED ARCHITECTURE FOR LAYERED HIDDEN MARKOV MODELS 审中-公开
    分层隐藏式MARKOV模型的分布式结构

    公开(公告)号:US20140222731A1

    公开(公告)日:2014-08-07

    申请号:US13955722

    申请日:2013-07-31

    CPC classification number: G06N20/00

    Abstract: In one embodiment, techniques are shown and described relating to a distributed architecture for layered Hidden Markov Models. In particular, in one embodiment, a Hidden Markov Model (HMM) at a layer i receives a sequence of hidden state produced by an HMM at a layer i−1, and uses the sequence of hidden state produced by the HMM at layer i−1 as input to the HMM at layer i, where the HMM at layer i−1 uses first time period bins, and the HMM at layer i uses second time period bins that are greater in length than the first time period bins. In another embodiment, the HMM at layer i originates the input (e.g., from measured properties), and produces the sequence of hidden state to output it to an HMM at a layer i+1 for use as its input.

    Abstract translation: 在一个实施例中,与用于分层隐马尔可夫模型的分布式架构相关的技术被示出和描述。 特别地,在一个实施例中,层i处的隐马尔可夫模型(HMM)接收由层I-1上的HMM产生的隐藏状态序列,并且使用层i-1由HMM产生的隐藏状态序列, 1作为第i层的HMM的输入,其中层i-1处的HMM使用第一时间段仓,并且层i处的HMM使用长于第一时间段的长度的第二时间段仓。 在另一个实施例中,层i上的HMM产生输入(例如,从测量的属性),并且产生隐藏状态的序列以将其输出到层i + 1处的HMM用作其输入。

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