Detail publikace

GPON PLOAMd Message Analysis Using Supervised Neural Networks

TOMAŠOV, A. HOLÍK, M. OUJEZSKÝ, V. HORVÁTH, T. MÜNSTER, P.

Originální název

GPON PLOAMd Message Analysis Using Supervised Neural Networks

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This paper discusses the possibility of analyzing the orchestration protocol used in gigabit-capable passive optical networks (GPONs). Considering the fact that a GPON is defined by the International Telecommunication Union Telecommunication sector (ITU-T) as a set of recommendations, implementation across device vendors might exhibit few differences, which complicates analysis of such protocols. Therefore, machine learning techniques are used (e.g., neural networks) to evaluate differences in GPONs among various device vendors. As a result, this paper compares three neural network models based on different types of recurrent cells and discusses their suitability for such analysis.

Klíčová slova

GPON; GRU; LSTM; machine learning; neural network; RNN

Autoři

TOMAŠOV, A.; HOLÍK, M.; OUJEZSKÝ, V.; HORVÁTH, T.; MÜNSTER, P.

Vydáno

18. 11. 2020

Nakladatel

MDPI

Místo

Švýcarsko

ISSN

2076-3417

Periodikum

Applied Sciences - Basel

Ročník

10

Číslo

22

Stát

Švýcarská konfederace

Strany od

1

Strany do

12

Strany počet

12

URL

https://www.mdpi.com/2076-3417/10/22/8139/htm

Plný text v Digitální knihovně

http://hdl.handle.net/11012/196655

BibTex

@article{BUT166029,
  author="Adrián {Tomašov} and Martin {Holík} and Václav {Oujezský} and Tomáš {Horváth} and Petr {Münster}",
  title="GPON PLOAMd Message Analysis Using Supervised Neural Networks
",
  journal="Applied Sciences - Basel",
  year="2020",
  volume="10",
  number="22",
  pages="1--12",
  doi="10.3390/app10228139",
  issn="2076-3417",
  url="https://www.mdpi.com/2076-3417/10/22/8139/htm"
}