Forecasting Internet Traffic by Neural Networks Under Univariate and Multivariate Strategies

Paulo Cortez, Miguel Rio, Pedro Sousa, Miguel Rocha

Abstract

By improving Internet traffic forecasting, more efficient TCP/IP traffic control and anomaly detection tools can be developed, leading to economic gains due to better resource management. In this paper, Neural Networks (NNs) are used to predict TCP/IP traffic for 39 links of the UK education and research network, under univariate and multivariate strategies. The former uses only past values of the forecasted link, while the latter also uses the traffic from neighbor links of the network topology. Several experiments were held by considering hourly real-world data. The Holt-Winters method was also tested in the comparison. Overall, the univariate NN approach produces the best forecasts for the backbone links, while a Dijkstra based NN multivariate strategy is the best option for the core to subnetwork links.

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Paper Citation


in Harvard Style

Cortez P., Rio M., Sousa P. and Rocha M. (2008). Forecasting Internet Traffic by Neural Networks Under Univariate and Multivariate Strategies . In Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008) ISBN 978-989-8111-33-3, pages 61-70. DOI: 10.5220/0001508600610070


in Bibtex Style

@conference{anniip08,
author={Paulo Cortez and Miguel Rio and Pedro Sousa and Miguel Rocha},
title={Forecasting Internet Traffic by Neural Networks Under Univariate and Multivariate Strategies},
booktitle={Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008)},
year={2008},
pages={61-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001508600610070},
isbn={978-989-8111-33-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008)
TI - Forecasting Internet Traffic by Neural Networks Under Univariate and Multivariate Strategies
SN - 978-989-8111-33-3
AU - Cortez P.
AU - Rio M.
AU - Sousa P.
AU - Rocha M.
PY - 2008
SP - 61
EP - 70
DO - 10.5220/0001508600610070