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11.发明申请公开(公告)号：US20210056463A1
公开(公告)日：2021-02-25
申请号：US16548710
申请日：2019-08-22
Applicant: Cisco Technology, Inc.
Inventor： Erwan Barry Tarik Zerhouni , Abhishek Kumar , Javier Cruz Mota
Abstract: The disclosed technology relates to a process of providing dynamic machine learning on premise model selection. In particular, a set of machine learned models are generated and provided to an on premise computing device. The machine learned models are generated using a cluster of customer data (e.g. telemetric data) stored on a computing network having different ranges of computational complexity. One of the machine learned models from the set of machine learned models will be selected based on the current available computational resources detected at the on premise computing device. Different machine learned models from the set of machine learned models can then be selected based on changes in the available computational resources and/or customer feedback
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12.发明申请公开(公告)号：US20190342194A1
公开(公告)日：2019-11-07
申请号：US15967668
申请日：2018-05-01
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur , Abhishek Kumar
Abstract: In one embodiment, a network assurance service that monitors a network detects anomalies in the network by applying one or more machine learning models to telemetry data from the network. The network assurance service ranks feedback from a plurality of anomaly rankers regarding relevancy or criticality of the detected anomalies. The network assurance service clusters the plurality of anomaly rankers into clusters of similar rankers, based on the received ranking feedback. The network assurance service uses the clusters of similar rankers to assign reliability scores to each of the anomaly rankers. The network assurance service selects, based on the reliability scores, a subset of the plurality of anomaly rankers to receive an anomaly detection alert regarding a particular detected anomaly to be ranked. The network assurance service provides the anomaly detection alert to the selected subset of the plurality of anomaly rankers for ranking.
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公开(公告)号：US20190215230A1
公开(公告)日：2019-07-11
申请号：US15864565
申请日：2018-01-08
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Abhishek Kumar , Jean-Philippe Vasseur
IPC: H04L12/24
Abstract: In one embodiment, a network assurance system discretizes parameter values of a plurality of time series of measurements obtained from a monitored network by assigning tags to the parameter values. The network assurance system detects occurrences of a particular type of failure event in the monitored network. The network assurance system identifies a set of the assigned tags that frequently co-occur with the occurrences of the particular type of failure event. The network assurance system determines, using a Bayesian framework, rankings for the tags in the identified set based on how well each of the tags acts as a predictor of the failure event. The network assurance system initiates performance of a corrective measure for the failure event based in part on the determined rankings for the tags in the identified set.
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公开(公告)号：US20170026468A1
公开(公告)日：2017-01-26
申请号：US14805078
申请日：2015-07-21
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Kumar , Harmanpreet Singh , Kamalkrishna Rameshan , Moiz Raja
CPC classification number: H04L67/1095 , H04L45/00 , H04L45/02 , H04L45/16 , H04L51/14 , H04L51/32 , H04L63/0272 , H04L67/104 , H04L67/327 , H04L67/40 , H04L69/28
Abstract: Systems, methods, and computer-readable media for an adaptive gossip protocol. A node in a cluster can detect a gossip protocol synchronization triggering event which can include an indication that the node has received data from a second node via a gossip protocol, an update to data maintained by nodes in the cluster, and/or an operation. In response to the triggering event, the node can determine a dynamic gossip interval for disseminating data from the node to other nodes via a gossip protocol, the dynamic gossip interval being based on a synchronization state associated with the cluster and/or one or more gossip protocol events associated with the cluster. Next, the node can select a third node in the cluster for disseminating the data from the node to the third node. The node can then transmit the data to the third node via the gossip protocol based on the dynamic gossip interval.
Abstract translation: 用于自适应八卦协议的系统，方法和计算机可读介质。 集群中的节点可以检测八卦协议同步触发事件，其可以包括节点已经经由八卦协议从第二节点接收数据的指示，对簇中的节点维护的数据的更新和/或操作。 响应于触发事件，节点可以通过八卦协议来确定用于从节点传播数据到其他节点的动态八卦间隔，动态八卦间隔基于与群集相关联的同步状态和/或一个或多个八卦 与集群关联的协议事件。 接下来，节点可以选择集群中的第三节点，用于将数据从节点传播到第三节点。 然后，节点可以基于动态八卦间隔通过八卦协议将数据发送到第三节点。
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15.发明授权公开(公告)号：US11769075B2
公开(公告)日：2023-09-26
申请号：US16548710
申请日：2019-08-22
Applicant: Cisco Technology, Inc.
Inventor： Erwan Barry Tarik Zerhouni , Abhishek Kumar , Javier Cruz Mota
IPC: G06N20/00 , G06Q10/067
CPC classification number: G06N20/00 , G06Q10/067
Abstract: The disclosed technology relates to a process of providing dynamic machine learning on premise model selection. In particular, a set of machine learned models are generated and provided to an on premise computing device. The machine learned models are generated using a cluster of customer data (e.g. telemetric data) stored on a computing network having different ranges of computational complexity. One of the machine learned models from the set of machine learned models will be selected based on the current available computational resources detected at the on premise computing device. Different machine learned models from the set of machine learned models can then be selected based on changes in the available computational resources and/or customer feedback.
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Patent Agency Ranking
公开(公告)号：US20200293942A1
公开(公告)日：2020-09-17
申请号：US16298881
申请日：2019-03-11
Applicant: Cisco Technology, Inc.
Inventor： Robert Edgar Barton , Jerome Henry , Abhishek Kumar
IPC: G06N20/00
Abstract: The disclosed technology relates to a process for metered training of fog nodes within the fog layer. The metered training allows the fog nodes to be continually trained within the fog layer without the need for the cloud. Furthermore, the metered training allows the fog node to operate normally as the training is performed only when spare resources are available at the fog node. The disclosed technology also relates to a process of sharing better trained machine learning models of a fog node with other similar fog nodes thereby speeding up the training process for other fog nodes within the fog layer.
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公开(公告)号：US10091087B2
公开(公告)日：2018-10-02
申请号：US14804195
申请日：2015-07-20
Applicant: Cisco Technology, Inc.
Inventor： Moiz Raja , Abhishek Kumar , Kamalkrishna Rameshan , Harmanpreet Singh
IPC: G06F17/30 , H04L12/26 , H04L12/803
Abstract: Disclosed are systems, methods, and computer-readable storage media for load balance resources amongst computing nodes. Various embodiments of the present technology can be used to, prior to assigning a first data shard included in a first cluster of data shards as a leader of the first cluster of data shards, determine whether a first computing node storing the first data shard also stores a second data shard designated as a leader of a second cluster of data shards, yielding a determination, and when the determination indicates that the first computing node stores the second data shard designated as the leader of the second cluster of data shards, designate the first data shard as non-electable to be the leader of the first cluster of data shards and electing an alternate data shard included in the first cluster of data shards as the leader of the first cluster of data shards.
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公开(公告)号：US20170024453A1
公开(公告)日：2017-01-26
申请号：US14804195
申请日：2015-07-20
Applicant: Cisco Technology, Inc.
Inventor： Moiz Raja , Abhishek Kumar , Kamalkrishna Rameshan , Harmanpreet Singh
IPC: G06F17/30 , H04L12/26 , H04L12/803
CPC classification number: H04L43/16 , G06F17/30584 , H04L41/0896 , H04L47/125
Abstract: Disclosed are systems, methods, and computer-readable storage media for load balance resources amongst computing nodes. Various embodiments of the present technology can be used to, prior to assigning a first data shard included in a first cluster of data shards as a leader of the first cluster of data shards, determine whether a first computing node storing the first data shard also stores a second data shard designated as a leader of a second cluster of data shards, yielding a determination, and when the determination indicates that the first computing node stores the second data shard designated as the leader of the second cluster of data shards, designate the first data shard as non-electable to be the leader of the first cluster of data shards and electing an alternate data shard included in the first cluster of data shards as the leader of the first cluster of data shards.
Abstract translation: 公开了用于计算节点之间的负载平衡资源的系统，方法和计算机可读存储介质。 可以使用本技术的各种实施例，在将包括在第一数据分片簇中的第一数据分片分配为第一数据分片簇的前导者之前，确定存储第一数据分片的第一计算节点是否也存储 指定为第二数据分片簇的引导者的第二数据分片，产生确定，并且当确定指示第一计算节点存储指定为第二数据分片簇的前导的第二数据片时，指定第一数据分片 数据分片不可选择成为第一个数据分片集群的领导者，并选择第一个数据分片集群中包含的备用数据分片作为第一个数据分片集群的领导者。
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19.发明申请公开(公告)号：US20210075707A1
公开(公告)日：2021-03-11
申请号：US16563472
申请日：2019-09-06
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Kumar , Erwan Barry Tarik Zerhouni , Javier Cruz Mota
IPC: H04L12/26
Abstract: Technologies for dynamically generating topology and location based network insights are provided. In some examples, a method can include determining statistical changes in time series data including a series of data points associated with one or more conditions or parameters of a network; determining a period of time corresponding to one or more of the statistical changes in the time series data; obtaining telemetry data corresponding to a segment of the network and one or more time intervals, wherein a respective length of each time interval is based on a length of the period of time corresponding to the one or more of the statistical changes in the time series data; and generating, based on the telemetry data, insights about the segment of the network, the insights identifying a trend or statistical deviation in a behavior of the segment of the network during the one or more time intervals.
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20.发明授权公开(公告)号：US10680919B2
公开(公告)日：2020-06-09
申请号：US15967668
申请日：2018-05-01
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur , Abhishek Kumar
Abstract: In one embodiment, a network assurance service that monitors a network detects anomalies in the network by applying one or more machine learning models to telemetry data from the network. The network assurance service ranks feedback from a plurality of anomaly rankers regarding relevancy or criticality of the detected anomalies. The network assurance service clusters the plurality of anomaly rankers into clusters of similar rankers, based on the received ranking feedback. The network assurance service uses the clusters of similar rankers to assign reliability scores to each of the anomaly rankers. The network assurance service selects, based on the reliability scores, a subset of the plurality of anomaly rankers to receive an anomaly detection alert regarding a particular detected anomaly to be ranked. The network assurance service provides the anomaly detection alert to the selected subset of the plurality of anomaly rankers for ranking.
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