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Registered METHOD AND APPARATUS FOR ALLOCATING BANDWIDTH BASED ON MACHINE LEARNING IN PASSIVE OPTICAL NETWORK

Inventors
Oh Jung-Yeol, Chung Hwan Seok, Lee Han Hyub, Doo Kyeong Hwan
Application No.
16207300 (2018.12.03)
Publication No.
20200092622 (2020.03.19)
Registration No.
11412317 (2022.08.09)
Country
UNITED STATES
Project Code
18HH2200, SDN based Wired and wireless converged optical Access Networking, Chung Hwan Seok
Abstract
A method and apparatus for allocating a bandwidth based on machine learning in a passive optical network, the method including generating an inference model to predict a consumed bandwidth required for transmission by learning unstructured data of a PON including an OLT and traffic data corresponding to state information of the PON collected from the PON, predicting a consumed bandwidth with respect to a queue corresponding to a class requiring a low-latency service among classes of ONUS connected to the OLT based on the generated inference model, performing a VBA with respect to the queue corresponding to the class requiring the low-latency service based on the predicted consumed bandwidth, and performing a DBA with respect to a queue corresponding to a class not requiring the low-latency service using a transmission bandwidth which remains after the VBA is performed.
KSP Keywords
Low latency, Optical network, Passive optical network, State information, Unstructured Data, inference model, machine Learning, traffic data, transmission bandwidth
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Status Patent Country KIPRIS
Registered 수동형 광 네트워크에서의 기계학습 기반 대역 할당 방법 및 장치 KOREA KIPRIS