polito.it
Politecnico di Torino (logo)

A Deep Learning Analysis of Internet Traffic Datasets for 5G MEC Dimensioning

Luigi Fabiano

A Deep Learning Analysis of Internet Traffic Datasets for 5G MEC Dimensioning.

Rel. Claudio Ettore Casetti. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2020

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (3MB) | Preview
Abstract:

This thesis work consists in studying Deep Learning models in order to predict, as well as possible, the Internet traffic in a mobile network environment and use them in the 5G context for MEC (Multi-access Edge Computing) dimensioning. In particular, the first chapter gives a brief introduction about AI and Machine Learning. Basic concepts needed to understand the mechanism behind Deep Learning are provided through the second chapter. Third chapter supplies a description of used dataset. Analysis and results of DL models are presented in chapter four. Finally, the last chapter shows an application of the whole study for MEC dimensioning.

Relators: Claudio Ettore Casetti
Academic year: 2019/20
Publication type: Electronic
Number of Pages: 88
Subjects:
Corso di laurea: Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni)
Classe di laurea: New organization > Master science > LM-27 - TELECOMMUNICATIONS ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/14396
Modify record (reserved for operators) Modify record (reserved for operators)