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In this paper, we consider computer network traffic analysis. We analyze real data captured from a computer network and based on them, we generate predictions of the network traffic load. We propose two neural architectures based on temporal convolutional network (TCN) and long short-term memory network (LSTM). Experimental evaluation enhanced by a statistical analysis confirmed the reliability of the proposed networks.

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Evaluating Neural Network Models for Accurate Prediction of Network Traffic Load

  • 会议论文

  • 发表日期：

    2025年

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  • Jarosław Bernacki,
  • Kelton A. P. Costa,
  • Katarzyna Nieszporek

摘要

In this paper, we consider computer network traffic analysis. We analyze real data captured from a computer network and based on them, we generate predictions of the network traffic load. We propose two neural architectures based on temporal convolutional network (TCN) and long short-term memory network (LSTM). Experimental evaluation enhanced by a statistical analysis confirmed the reliability of the proposed networks.