公开(公告)号：US20190190815A1

公开(公告)日：2019-06-20

申请号：US15845291

申请日：2017-12-18

Applicant: Cisco Technology, Inc.

Inventor： Pascal Thubert ,  Enzo Fenoglio ,  Jean-Philippe Vasseur ,  Hugo Latapie

IPC: H04L12/751 ,  H04L12/725 ,  H04L12/707 ,  H04L12/851 ,  H04L12/24

CPC classification number: H04L45/08 ,  H04L41/147 ,  H04L45/22 ,  H04L45/302 ,  H04L47/2441

Abstract: In one embodiment, a controller in a network trains a deep reinforcement learning-based agent to predict traffic flows in the network. The controller determines one or more resource requirements for the predicted traffic flows. The controller assigns, using the deep reinforcement learning-based agent, paths in the network to the flows based on the determined one or more resource requirements, to avoid fragmentation of a flow during transmission of the flow through the network. The controller sends, to nodes in the network, assignment instructions that cause the flows to traverse the network via their assigned paths.

公开(公告)号：US20180027309A1

公开(公告)日：2018-01-25

申请号：US15660882

申请日：2017-07-26

Applicant: Cisco Technology, Inc.

Inventor： Joseph Friel ,  Hugo Latapie ,  Andre Surcouf ,  Enzo Fenoglio

IPC: H04Q9/00

CPC classification number: H04Q9/00 ,  G08C25/00

Abstract: Disclosed are systems, methods, and computer-readable storage media for adaptive telemetry based on in-network cross domain intelligence. A telemetry server can receive at least a first telemetry data stream and a second telemetry data stream. The first telemetry data stream can provide data collected from a first data source and the second telemetry data stream can provide data collected from a second data source. The telemetry server can determine correlations between the first telemetry data stream and the second telemetry data stream that indicate redundancies between data included in the first telemetry data stream and the second telemetry data stream, and then adjust, based on the correlations between the first telemetry data stream and the second telemetry data stream, data collection of the second telemetry data stream to reduce redundant data included in the first telemetry data stream and the second telemetry data stream.

公开(公告)号：US20170366425A1

公开(公告)日：2017-12-21

申请号：US15185157

申请日：2016-06-17

Applicant: Cisco Technology, Inc.

Inventor： Hugo Latapie ,  Enzo Fenoglio ,  Plamen Nedeltchev ,  Manikandan Kesavan ,  Joseph Friel

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

CPC classification number: H04L67/306 ,  H04L41/046 ,  H04L41/145 ,  H04L41/16 ,  H04L43/026 ,  H04L43/04 ,  H04L67/02 ,  H04L67/2804 ,  H04L67/327

Abstract: In one embodiment, a device in a network monitors a plurality of traffic flows in the network. The device extracts a plurality of features from the monitored plurality of traffic flows. The device generates a context model by using deep learning and reinforcement learning on the plurality of features extracted from the monitored traffic flows. The device applies the context model to a particular traffic flow associated with a client, to determine a context for the particular traffic flow. The device personalizes data sent to the client from a remote source based on the determined context.