Resumen

LEON, D. A.; MARTINEZQ, J. G.; ARDILA, I. A.  y  MOSQUERA, D. J.. Artificial intelligence for traffic control in data networks: A Review. Entre Ciencia e Ingenieria [online]. 2022, vol.16, n.31, pp.17-24.  Epub 15-Jul-2023. ISSN 1909-8367.  https://doi.org/10.31908/19098367.2655.

Traffic control in data networks has recently become very important due to the massive use of computer networks in different areas of society. Different techniques are usually used to carry out effective traffic control, allowing, among other things, to classify, predict and monitor network traffic. These techniques have evolved and are currently supported by artificial intelligence tools, which have made it possible to improve the results obtained with conventional techniques. This paper collects the different contributions made by the field of artificial intelligence to the improvement of these techniques and network management in general. The article describes the contributions made in aspects such as security, prediction, and classification of data traffic, as well as the optimization of routing in a computer network.

Palabras clave : Traffic management; traffic control techniques; artificial intelligence; machine learning; deep learning.

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