公开(公告)号：US20150195149A1

公开(公告)日：2015-07-09

申请号：US14164425

申请日：2014-01-27

Applicant: Cisco Technology, Inc.

Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Sukrit Dasgupta

IPC: H04L12/24 ,  H04L12/851

CPC classification number: H04L41/5009 ,  G06N7/005 ,  G06N99/005 ,  G06Q10/04 ,  H04L41/12 ,  H04L41/147 ,  H04L41/16 ,  H04L41/5019 ,  H04L47/2425

Abstract: In one embodiment, a request to make a prediction regarding one or more service level agreements (SLAs) in a network is received. A network traffic parameter and an SLA requirement associated with the network traffic parameter according to the one or more SLAs are also determined. In addition, a performance metric associated with traffic in the network that corresponds to the determined network traffic parameter is estimated. It may then be predicted whether the SLA requirement would be satisfied based on the estimated performance metric.

Abstract translation: 在一个实施例中，接收到关于网络中的一个或多个服务水平协议（SLA）进行预测的请求。 还确定了与根据一个或多个SLA的网络流量参数相关联的网络流量参数和SLA要求。 此外，估计与确定的网络流量参数对应的网络中的流量相关联的性能指标。 然后可以基于估计的性能度量来预测是否满足SLA要求。

公开(公告)号：US20140222996A1

公开(公告)日：2014-08-07

申请号：US13941063

申请日：2013-07-12

Applicant: Cisco Technology, Inc.

Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Sukrit Dasgupta

IPC: H04L12/26

CPC classification number: H04L43/02 ,  H04L41/16 ,  H04L43/103 ,  Y04S40/168

Abstract: In one embodiment, techniques are shown and described relating to dynamically adjusting a set of monitored network properties using distributed learning machine feedback. In particular, in one embodiment, a learning machine (or distributed learning machines) determines a plurality of monitored network properties in a computer network. From this, a subset of relevant network properties of the plurality of network properties may be determined, such that a corresponding subset of irrelevant network properties based on the subset of relevant network properties may also be determined. Accordingly, the computer network may be informed of the irrelevant network properties to reduce a rate of monitoring the irrelevant network properties.

Abstract translation: 在一个实施例中，示出和描述了关于使用分布式学习机器反馈动态地调整一组被监控的网络属性的技术。 特别地，在一个实施例中，学习机器（或分布式学习机器）在计算机网络中确定多个被监控的网络属性。 由此，可以确定多个网络属性的相关网络属性的子集，使得也可以确定基于相关网络属性子集的不相关网络属性的对应子集。 因此，可以向计算机网络通知不相关的网络属性，以降低监视不相关网络属性的速率。

公开(公告)号：US20140222975A1

公开(公告)日：2014-08-07

申请号：US13948367

申请日：2013-07-23

Applicant: Cisco Technology, Inc.

Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Sukrit Dasgupta

IPC: H04L12/26

CPC classification number: H04L41/16 ,  H04L41/142

Abstract: In one embodiment, techniques are shown and described relating to learning machine based computation of network join times. In particular, in one embodiment, a device computes a join time of the device to join a computer network. During joining, the device sends a configuration request to a server, and receives instructions whether to provide the join time. The device may then provide the join time to a collector in response to instructions to provide the join time. In another embodiment, a collector receives a plurality of join times from a respective plurality of nodes having one or more associated node properties. The collector may then estimate a mapping between the join times and the node properties and determines a confidence interval of the mapping. Accordingly, the collector may then determine a rate at which nodes having particular node properties report their join times based on the confidence interval.

Abstract translation: 在一个实施例中，与基于学习机的网络连接时间的计算相关的技术被示出和描述。 特别地，在一个实施例中，设备计算设备加入计算机网络的加入时间。 在加入过程中，设备向服务器发送配置请求，并接收指令是否提供加入时间。 响应于提供加入时间的指令，设备可以向收集器提供加入时间。 在另一个实施例中，收集器从具有一个或多个关联节点属性的相应多个节点接收多个连接时间。 然后，收集器可以估计连接时间和节点属性之间的映射，并确定映射的置信区间。 因此，收集器然后可以基于置信区间来确定具有特定节点属性的节点报告其连接时间的速率。

公开(公告)号：US20140222725A1

公开(公告)日：2014-08-07

申请号：US13926526

申请日：2013-06-25

Applicant: Cisco Technology, Inc.

Inventor： Jean-Philippe Vasseur ,  Sukrit Dasgupta ,  Jonathan W. Hui ,  Grégory Mermoud

IPC: G06N99/00

CPC classification number: G06N99/005

Abstract: In one embodiment, a node receives a request to initiate a shadow joining operation to shadow join a field area router (FAR) of a computer network, and preserves its data structures and soft states. The shadow joining operation may then be initiated to shadow join the FAR, wherein shadow joining comprises preforming join operations without leaving a currently joined-FAR, and the node measures one or more joining metrics of the shadow joining operation, and reports them accordingly. In another embodiment, a FAR (or other management device) determines a set of nodes to participate in a shadow joining operation, and informs the set of nodes of the shadow joining operation to shadow join the FAR. The device (e.g., FAR) participates in the shadow joining operation, and receives reports of one or more joining metrics of the shadow joining operation measured by the set of nodes.

Abstract translation: 在一个实施例中，节点接收发起影子加入操作以影响连接计算机网络的场区域路由器（FAR）的请求，并保留其数据结构和软状态。 然后可以启动阴影加入操作以影子连接FAR，其中阴影连接包括预先加入连接操作而不离开当前连接的FAR，并且节点测量阴影加入操作的一个或多个连接度量，并相应地报告。 在另一个实施例中，FAR（或其他管理设备）确定参与阴影加入操作的一组节点，并且通知该组节点的阴影加入操作以影响加入FAR。 设备（例如，FAR）参与阴影加入操作，并且接收由该组节点测量的阴影加入操作的一个或多个连接度量的报告。

公开(公告)号：US20140219133A1

公开(公告)日：2014-08-07

申请号：US13934929

申请日：2013-07-03

Applicant: Cisco Technology, Inc.

Inventor： Sukrit Dasgupta ,  Jean-Philippe Vasseur ,  Grégory Mermoud

IPC: H04L12/861

CPC classification number: H04L49/9057 ,  H04L47/28

Abstract: In one embodiment, a message is received at a node in a network indicating that the node is classified as a critical node, and requesting the node to proactively time-stamp data packets. Data packets are received from one or more child nodes of the node, and the node selects a data packet of the received data packets to time-stamp. Then, the node proactively inserts a time-stamp in the selected data packet. The time-stamped data packet is sent toward a central management node.

Abstract translation: 在一个实施例中，在网络中的节点处接收到指示节点被分类为关键节点并且请求节点主动地对数据分组进行时间戳的消息。 从节点的一个或多个子节点接收数据分组，并且节点选择所接收的数据分组的数据分组进行时间戳。 然后，节点主动地在选择的数据分组中插入时间戳。 时间戳数据包被发送到中央管理节点。

公开(公告)号：US20250015949A1

公开(公告)日：2025-01-09

申请号：US18766451

申请日：2024-07-08

Applicant: Cisco Technology, Inc.

Inventor： Jerome Henry ,  Pascal Thubert ,  Jean Philippe Vasseur ,  Federico Lovison ,  Sukrit Dasgupta

IPC: H04L5/00 ,  H04W84/12

Abstract: Optimizing or otherwise improving sounding intervals may be provided. Improving sounding intervals can include generating predicted Channel State information (CSI) of a Station (STA). A Null Data Packet (NDP) Announcement (NDPA) can be sent to the STA, wherein the NDPA instructs the STA to send compressed CSI. A reference signal is then sent to the STA. Finally, the compressed CSI is received from the STA.

公开(公告)号：US20240306054A1

公开(公告)日：2024-09-12

申请号：US18600414

申请日：2024-03-08

Applicant: Cisco Technology, Inc.

Inventor： Federico Lovison ,  Sukrit Dasgupta

IPC: H04W36/00 ,  H04W16/18

CPC classification number: H04W36/00835 ,  H04W16/18

Abstract: Roaming optimization, and particularly transmitting directional neighbor reports to optimize roaming may be provided. For roaming optimization, it is first determined that a client is going to roam to a new Access Point (AP). In response to determining the client is going to roam to a new AP, an estimated path of the client is determined. One or more candidate APs are determined based at least in part on the estimated path, and probabilities of roaming to the one or more candidate APs is determined based at least in part on the estimated path. A directional neighbor report including a list of the one or more candidate APs and the probabilities is generated and transmitted to the client.

公开(公告)号：US11797883B2

公开(公告)日：2023-10-24

申请号：US16809060

申请日：2020-03-04

Applicant: Cisco Technology, Inc.

Inventor： Andrea Di Pietro ,  Javier Cruz Mota ,  Sukrit Dasgupta ,  Jean-Philippe Vasseur

IPC: G06F15/16 ,  G06N20/00 ,  H04L41/22 ,  H04L41/14 ,  G06N5/04 ,  H04L41/16 ,  G06F15/173

CPC classification number: G06N20/00 ,  G06N5/04 ,  H04L41/14 ,  H04L41/16 ,  H04L41/22

Abstract: In one embodiment, a service receives telemetry data collected from a plurality of different networks. The service combines the telemetry data into a synthetic input trace. The service inputs the synthetic input trace into a plurality of machine learning models to generate a plurality of predicted key performance indicators (KPIs), each of the models having been trained to assess telemetry data from an associated network in the plurality of different networks and predict a KPI for that network. The service compares the plurality of predicted KPIs to identify one of the plurality of different networks as exhibiting an abnormal behavior.

公开(公告)号：US20210306224A1

公开(公告)日：2021-09-30

申请号：US16831200

申请日：2020-03-26

Applicant: Cisco Technology, Inc.

Inventor： Andrea Di Pietro ,  Sukrit Dasgupta

IPC: H04L12/24 ,  G06N20/00 ,  H04L29/08 ,  H04L12/26

Abstract: The present technology allows a hybrid approach to using artificial intelligence engines to perform issue generation, leveraging both on-premise and cloud components. In the technology, a cloud-based computing device receives data associated with a computing network of devices and uses machine-learning to create a model of the computing network. The cloud-based computing device communicates the model to a computing system located on-premise with the computing network and receives data related to the issues and insights created by the on-premise computing system. The cloud-based computing device determines if the on-premise computing system is producing issues and insights below a threshold quality. If yes, the cloud-based computing device updates the model based on updated data associated with the computing network and communicates the updated model to the on-premise computing system.

公开(公告)号：US10484405B2

公开(公告)日：2019-11-19

申请号：US14603978

申请日：2015-01-23

Applicant: Cisco Technology, Inc.

Inventor： Sukrit Dasgupta ,  Jean-Philippe Vasseur

IPC: H04L29/06

Abstract: In one embodiment, a first device in a network identifies an anomalous traffic flow in the network. The first device reports the anomalous traffic flow to a supervisory device in the network. The first device determines a quarantine policy for the anomalous traffic flow. The first device determines an action policy for the anomalous traffic flow. The first device applies the quarantine and action policies to one or more packets of the anomalous traffic flow.