Invention Grant
- Patent Title: Forecasting SDN fabric saturation and machine learning-based flow admission control
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Application No.: US17002003Application Date: 2020-08-25
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Publication No.: US11381518B2Publication Date: 2022-07-05
- Inventor: Patrick Wetterwald , Pascal Thubert , Jean-Philippe Vasseur , Eric Levy-Abegnoli , Stephane Labetoulle
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Behmke Innovation Group LLC
- Agent Kenneth J. Heywood; Jonathon P. Western
- Main IPC: H04L47/83
- IPC: H04L47/83 ; H04L47/127 ; G06N20/00 ; G06N5/04 ; H04L47/70
Abstract:
In one embodiment, a device of a software defined wide area network (SD-WAN) predicts characteristics of a new traffic flow to be admitted to the SD-WAN, based on a set of initial packets of the flow. The device predicts an impact of admitting the flow to the SD-WAN, based in part on extrinsic or exogenous data regarding the SD-WAN. The device admits the flow to the SD-WAN, based on the predicted impact. The supervisory device uses reinforcement learning to adjust one or more call admission control (CAC) parameters of the SD-WAN, based on captured telemetry data regarding the admitted flow.
Information query
