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Barona López, Lorena Isabel and Maestre Vidal, Jorge and García Villalba, Luis Javier (2017) An Approach to Data Analysis in 5G Networks. Entropy, 19 (2). p. 74. ISSN 1099-4300
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Official URL: https://doi.org/10.3390/e19020074
Abstract
5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET) Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.
Item Type: | Article |
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Uncontrolled Keywords: | 5G; data analysis; network function virtualization; situational awareness; software defined networking |
Subjects: | Sciences > Computer science > Artificial intelligence Sciences > Computer science > Internet Sciences > Computer science > Computer networks Sciences > Computer science > Software |
ID Code: | 67589 |
Deposited On: | 01 Sep 2021 07:48 |
Last Modified: | 06 Sep 2021 09:10 |
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