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LoRaWAN Behaviour Analysis through Dataset Traffic Investigation
The large development of Internet of Things technologies is increasing the use of smart-devices to solve and support several real-life issues. In many cases, the aim is to move toward systems that, even if significant demands are not required in terms of quantity of exchanged data, they should be ve...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003208/ https://www.ncbi.nlm.nih.gov/pubmed/35408085 http://dx.doi.org/10.3390/s22072470 |
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author | Spadaccino, Pietro Crinó, Francesco Giuseppe Cuomo, Francesca |
author_facet | Spadaccino, Pietro Crinó, Francesco Giuseppe Cuomo, Francesca |
author_sort | Spadaccino, Pietro |
collection | PubMed |
description | The large development of Internet of Things technologies is increasing the use of smart-devices to solve and support several real-life issues. In many cases, the aim is to move toward systems that, even if significant demands are not required in terms of quantity of exchanged data, they should be very reliable in terms of battery life and signal coverage. Networks that have these characteristics are the Low Power WAN (LPWAN). One of the most interesting LPWAN is LoRaWAN. LoRaWAN is a network with four principal components: end-devices, gateways, network servers, and application servers. It uses a LoRa physical layer to exchange messages between end-devices and gateways that forward these messages, through classic TCP/IP protocol, to the network server. In this work, we analyse LoRa and LoRaWAN by looking at its transmission characteristics and network behaviour, respectively, explaining the role of its components and showing the message exchange. This analysis is performed through the exploration of a dataset taken from the literature collecting real LoRaWAN packets. The goal of the work is twofold: (1) to investigate, under different perspectives, how a LoRaWAN works and (2) to provide software tools that can be used in several other LoraWAN datasets to measure the network behaviour. We carry out six different analyses to look at the most important features of LoRaWAN. For each analysis we present the adopted measurement strategy as well as the obtained results in the specific use case. |
format | Online Article Text |
id | pubmed-9003208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90032082022-04-13 LoRaWAN Behaviour Analysis through Dataset Traffic Investigation Spadaccino, Pietro Crinó, Francesco Giuseppe Cuomo, Francesca Sensors (Basel) Article The large development of Internet of Things technologies is increasing the use of smart-devices to solve and support several real-life issues. In many cases, the aim is to move toward systems that, even if significant demands are not required in terms of quantity of exchanged data, they should be very reliable in terms of battery life and signal coverage. Networks that have these characteristics are the Low Power WAN (LPWAN). One of the most interesting LPWAN is LoRaWAN. LoRaWAN is a network with four principal components: end-devices, gateways, network servers, and application servers. It uses a LoRa physical layer to exchange messages between end-devices and gateways that forward these messages, through classic TCP/IP protocol, to the network server. In this work, we analyse LoRa and LoRaWAN by looking at its transmission characteristics and network behaviour, respectively, explaining the role of its components and showing the message exchange. This analysis is performed through the exploration of a dataset taken from the literature collecting real LoRaWAN packets. The goal of the work is twofold: (1) to investigate, under different perspectives, how a LoRaWAN works and (2) to provide software tools that can be used in several other LoraWAN datasets to measure the network behaviour. We carry out six different analyses to look at the most important features of LoRaWAN. For each analysis we present the adopted measurement strategy as well as the obtained results in the specific use case. MDPI 2022-03-23 /pmc/articles/PMC9003208/ /pubmed/35408085 http://dx.doi.org/10.3390/s22072470 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Spadaccino, Pietro Crinó, Francesco Giuseppe Cuomo, Francesca LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title | LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title_full | LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title_fullStr | LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title_full_unstemmed | LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title_short | LoRaWAN Behaviour Analysis through Dataset Traffic Investigation |
title_sort | lorawan behaviour analysis through dataset traffic investigation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003208/ https://www.ncbi.nlm.nih.gov/pubmed/35408085 http://dx.doi.org/10.3390/s22072470 |
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