Optimizing Communication Data Streams in Edge Computing Systems Using Bayesian Algorithms
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Nerea Gómez Larrakoetxea [1] ; Borja Sanz Urquijo [1]
;
Iker Pastor López
[1]
;
Jon García Barruetabeña
[1]
;
Pablo García Bringas
[1]
-
[1] Universidad de Deusto
Universidad de Deusto
Bilbao, España
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- Localización: 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021) / Hugo Sanjurjo González (ed. lit.), Iker Pastor López (ed. lit.) , Héctor Quintián Bringas (ed. lit.), Emilio Santiago Corchado Rodríguez (ed. lit.) , 2022, ISBN 978-3-030-87868-9, págs. 122-131
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
Due to companies’ awareness of the real value of data, the amount of data they handle has increased significantly in recent years [20]. In order to obtain value from the data collected in each company, Big Data and Data Analytics techniques have to be applied. In carrying out this analysis in order to obtain valuable information for the company, several issues related to the computing power of the machines often emerge due to the high volume of data collected. In this paper we emphasis the importance of processing data effectively through data compression and an approach that can help to achieve this. In particular, we have used Bayesian networks to perform data compression without missing useful information.
