Framework for Behavioral Analysis of Mobile Networks
The arrival of the Fifth Generation (5G) entails a significant evolution in the context of mobile communication networks. This new technology will bring heterogeneous scenarios with new types of services and an increasingly high number of users and nodes. The efficient management of such complex net...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/10/3347 |
| _version_ | 1827692766668259328 |
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| author | José Antonio Trujillo Isabel de-la-Bandera David Palacios Raquel Barco |
| author_facet | José Antonio Trujillo Isabel de-la-Bandera David Palacios Raquel Barco |
| author_sort | José Antonio Trujillo |
| collection | DOAJ |
| description | The arrival of the Fifth Generation (5G) entails a significant evolution in the context of mobile communication networks. This new technology will bring heterogeneous scenarios with new types of services and an increasingly high number of users and nodes. The efficient management of such complex networks has become an important challenge. To address this problem, automatic and efficient algorithms must be developed to facilitate operators’ management and optimization of their networks. These algorithms must be able to cope with a very high number of heterogeneous data and different types of scenarios. In this paper, a novel framework for a cellular network behavioral analysis and monitoring is presented. This framework is based on a combination of unsupervised and supervised machine learning techniques. The proposed system can analyze the behavior of cells and monitor them, searching for behavior changes over time. The information extracted by the framework can be used to improve subsequent management and optimization functions. |
| first_indexed | 2024-03-10T11:30:33Z |
| format | Article |
| id | doaj.art-4d5dc3a4ca5b44819d50a639ef187e4f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T11:30:33Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4d5dc3a4ca5b44819d50a639ef187e4f2023-11-21T19:16:25ZengMDPI AGSensors1424-82202021-05-012110334710.3390/s21103347Framework for Behavioral Analysis of Mobile NetworksJosé Antonio Trujillo0Isabel de-la-Bandera1David Palacios2Raquel Barco3Department of Communications Engineering, Universidad de Málaga, Campus de Teatinos, 29071 Málaga, SpainDepartment of Communications Engineering, Universidad de Málaga, Campus de Teatinos, 29071 Málaga, SpainTupl Spain, Tupl Inc., Campus de Teatinos, 29071 Málaga, SpainDepartment of Communications Engineering, Universidad de Málaga, Campus de Teatinos, 29071 Málaga, SpainThe arrival of the Fifth Generation (5G) entails a significant evolution in the context of mobile communication networks. This new technology will bring heterogeneous scenarios with new types of services and an increasingly high number of users and nodes. The efficient management of such complex networks has become an important challenge. To address this problem, automatic and efficient algorithms must be developed to facilitate operators’ management and optimization of their networks. These algorithms must be able to cope with a very high number of heterogeneous data and different types of scenarios. In this paper, a novel framework for a cellular network behavioral analysis and monitoring is presented. This framework is based on a combination of unsupervised and supervised machine learning techniques. The proposed system can analyze the behavior of cells and monitor them, searching for behavior changes over time. The information extracted by the framework can be used to improve subsequent management and optimization functions.https://www.mdpi.com/1424-8220/21/10/3347mobile communication networkscell behaviorSelf-Organizing Maps (SOM)Random Forest |
| spellingShingle | José Antonio Trujillo Isabel de-la-Bandera David Palacios Raquel Barco Framework for Behavioral Analysis of Mobile Networks Sensors mobile communication networks cell behavior Self-Organizing Maps (SOM) Random Forest |
| title | Framework for Behavioral Analysis of Mobile Networks |
| title_full | Framework for Behavioral Analysis of Mobile Networks |
| title_fullStr | Framework for Behavioral Analysis of Mobile Networks |
| title_full_unstemmed | Framework for Behavioral Analysis of Mobile Networks |
| title_short | Framework for Behavioral Analysis of Mobile Networks |
| title_sort | framework for behavioral analysis of mobile networks |
| topic | mobile communication networks cell behavior Self-Organizing Maps (SOM) Random Forest |
| url | https://www.mdpi.com/1424-8220/21/10/3347 |
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