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A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks

Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In...

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Autores principales: Cortés-Polo, David, Jimenez Gil, Luis Ignacio, González-Sánchez, José-Luis, Calle-Cancho, Jesús
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218910/
https://www.ncbi.nlm.nih.gov/pubmed/32316093
http://dx.doi.org/10.3390/s20082247
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author Cortés-Polo, David
Jimenez Gil, Luis Ignacio
González-Sánchez, José-Luis
Calle-Cancho, Jesús
author_facet Cortés-Polo, David
Jimenez Gil, Luis Ignacio
González-Sánchez, José-Luis
Calle-Cancho, Jesús
author_sort Cortés-Polo, David
collection PubMed
description Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In this sense, network analytics will increase the knowledge about the network and its interconnected devices, being a key feature especially with the increment in the number of physical things (sensors, actuators, smartphones, tablets, and so on). With this increment, the usage of online networking services and applications will grow, and network operators require to detect and analyze all issues related to the network. In this article, a methodology to analyze real network information provided by a network operator and acquire knowledge of the communications is presented. Various real data sets, provided by Telecom Italia, are analyzed to compare two different zones: one located in the urban area of Milan, Italy, and its surroundings, and the second in the province of Trento, Italy. These data sets describe different areas and shapes that cover a metropolitan area in the first case and a mainly rural area in the second case, which implies that these areas will have different comportments. To compare these comportments and group them in a single cluster set, a new technique is presented in this paper to establish a relationship between them and reduce those that could be similar.
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spelling pubmed-72189102020-05-22 A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks Cortés-Polo, David Jimenez Gil, Luis Ignacio González-Sánchez, José-Luis Calle-Cancho, Jesús Sensors (Basel) Article Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In this sense, network analytics will increase the knowledge about the network and its interconnected devices, being a key feature especially with the increment in the number of physical things (sensors, actuators, smartphones, tablets, and so on). With this increment, the usage of online networking services and applications will grow, and network operators require to detect and analyze all issues related to the network. In this article, a methodology to analyze real network information provided by a network operator and acquire knowledge of the communications is presented. Various real data sets, provided by Telecom Italia, are analyzed to compare two different zones: one located in the urban area of Milan, Italy, and its surroundings, and the second in the province of Trento, Italy. These data sets describe different areas and shapes that cover a metropolitan area in the first case and a mainly rural area in the second case, which implies that these areas will have different comportments. To compare these comportments and group them in a single cluster set, a new technique is presented in this paper to establish a relationship between them and reduce those that could be similar. MDPI 2020-04-16 /pmc/articles/PMC7218910/ /pubmed/32316093 http://dx.doi.org/10.3390/s20082247 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cortés-Polo, David
Jimenez Gil, Luis Ignacio
González-Sánchez, José-Luis
Calle-Cancho, Jesús
A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title_full A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title_fullStr A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title_full_unstemmed A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title_short A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
title_sort methodology for network analysis to improve the cyber-physicals communications in next-generation networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218910/
https://www.ncbi.nlm.nih.gov/pubmed/32316093
http://dx.doi.org/10.3390/s20082247
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