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ICANN
2007
Springer

Topology Aware Internet Traffic Forecasting Using Neural Networks

8 years 10 months ago
Topology Aware Internet Traffic Forecasting Using Neural Networks
Forecasting Internet traffic is receiving an increasing attention from the computer networks domain. Indeed, by improving this task efficient traffic engineering and anomaly detection tools can be developed, leading to economic gains due to better resource management. This paper presents a Neural Network (NN) approach to predict TCP/IP traffic for all links of a backbone network, using both univariate and multivariate strategies. The former uses only past values of the forecasted link, while the latter is based on the neighbor links of the backbone topology. Several experiments were held by considering real-world data from the UK education and research network. Also, different time scales (e.g. every ten minutes and hourly) were analyzed. Overall, the proposed NN approach outperformed other forecasting methods (e.g. Holt-Winters).
Paulo Cortez, Miguel Rio, Pedro Sousa, Miguel Roch
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2007
Where ICANN
Authors Paulo Cortez, Miguel Rio, Pedro Sousa, Miguel Rocha
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