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DOI: 10.14569/IJACSA.2025.0160207
PDF

Enhanced Network Bandwidth Prediction with Multi-Output Gaussian Process Regression

Author 1: Shude Chen
Author 2: Takayuki Nakachi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 2, 2025.

  • Abstract and Keywords
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Abstract: Modern network environments, especially in do-mains like 5G and IoT, exhibit highly dynamic and nonlinear traffic behaviors, posing significant challenges for accurate time series analysis and predictive modeling. Traditional approaches, including stochastic ARIMA and deep learning-based LSTM, frequently encounter difficulties in capturing rapid signal variations and inter-channel dependencies, often due to data sparsity or excessive computational cost. To address these issues, this paper proposes a Multi-Output Gaussian Process (MOGP) framework augmented with a novel signal processing strategy, where additional signals are generated by summing adjacent elements over multiple window sizes. Such multi-scale enrichment effectively leverages cross-channel correlations, enabling the MOGP model to discover complex temporal patterns in multi-channel data. Experimental results on real-world network traces highlight that the proposed method achieves consistently lower RMSE compared to conventional single-output or deep learning methods, thereby underscoring its value for robust bandwidth estimation. Our findings suggest that integrating MOGP with multi-scale augmentation holds promise for a wide range of predictive analytics applications, including resource allocation in 5G networks and traffic monitoring in IoT systems.

Keywords: Network traffic prediction; Multi-Output Gaussian Process (MOGP); signal processing; time series analysis; predictive modeling; multi-channel data; IoT traffic monitoring; 5G networks

Shude Chen and Takayuki Nakachi, “Enhanced Network Bandwidth Prediction with Multi-Output Gaussian Process Regression” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160207

@article{Chen2025,
title = {Enhanced Network Bandwidth Prediction with Multi-Output Gaussian Process Regression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160207},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160207},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {Shude Chen and Takayuki Nakachi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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