Aplicando Redes Neurais e Análise Temporal para Predição Adaptativa de Desempenho de Rede

• Silvio E. S. B. Ribeiro UECE
• Rafael A. Menezes UECE
• Ariel L. C. Portela UECE
• Thelmo P. Araújo UECE
• Rafael L. Gomes UECE

DOI: https://doi.org/10.5753/sbrc.2023.508

Abstract

Network monitoring services are performed by several companies and Internet Service Providers (ISPs), which provide results of regular performance tests, such as throughput, loss, and delay, among others. These measurements support knowing the behavior of the network, as well as obtaining information for strategic planning. However, these tools still need to evolve in order to encompass more complex activities, such as performance prediction, especially within the current context of elastic demand. Within this context, this paper presents an adaptive network performance prediction model based on Neural Networks and Time Series Analysis, enabling the identification of future network performance in specific periods, according to past network measurements. The experiments carried out, using real data from the National Education and Research Network (RNP), show that the proposed model reaches high levels of accuracy in prediction and overcomes the existing prediction models.

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