首页> 外国专利> HIDDEN MARKOV MODEL BASED ARCHITECTURE TO MONITOR NETWORK NODE ACTIVITIES AND PREDICT RELEVANT PERIODS

HIDDEN MARKOV MODEL BASED ARCHITECTURE TO MONITOR NETWORK NODE ACTIVITIES AND PREDICT RELEVANT PERIODS

机译:基于隐马尔可夫模型的体系结构来监控网络节点活动和预测相关期间

摘要

In one embodiment, techniques are shown and described relating to a Hidden Markov Model based architecture to monitor network node activities and predict relevant periods. In particular, in one embodiment, a device determines a statistical model for each of one or more singular-node traffic profiles (e.g., based on one or more Hidden Markov Models (HMMs) each corresponding to a respective one of the one or more traffic profiles). By analyzing respective traffic from individual nodes in a computer network, and matching the respective traffic against the statistical model for the one or more traffic profiles, the device may detecting a matching traffic profile for the individual nodes in a computer network. In addition, the device may predict relevant periods of traffic for the individual nodes by extrapolating a most-likely future sequence based on prior respective traffic of the individual nodes and the corresponding matching traffic profile.
机译:在一个实施例中,示出并描述了与基于隐马尔可夫模型的架构有关的技术,以监视网络节点活动并预测相关时段。特别地,在一个实施例中,设备针对一个或多个单节点流量简档中的每一个确定统计模型(例如,基于各自与一个或多个流量中的相应一个相对应的一个或多个隐马尔可夫模型(HMM)个人资料)。通过分析来自计算机网络中的各个节点的相应业务,并且针对一个或多个业务概况将统计数据与相应的业务进行匹配,设备可以检测计算机网络中的各个节点的匹配业务概况。另外,该设备可以通过基于各个节点的先前各自的流量和对应的匹配流量简档外推最可能的未来序列来预测各个节点的相关流量时段。

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