Publication detail

GPON PLOAMd Message Analysis Using Supervised Neural Networks

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

Original Title

GPON PLOAMd Message Analysis Using Supervised Neural Networks

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

18. 11. 2020

Publisher

MDPI

Location

Švýcarsko

ISBN

2076-3417

Periodical

Applied Sciences - Basel

Year of study

10

Number

22

State

Swiss Confederation

Pages from

1

Pages to

12

Pages count

12

URL

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

Full text in the Digital Library

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"
}