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|Title:||End-to-end diagnosis of QoS violations with neural network||Authors:||Zhou, L.
|Issue Date:||2008||Citation:||Zhou, L.,Chen, L.,Hung, K.P.,Lek, H.N. (2008). End-to-end diagnosis of QoS violations with neural network. Proceedings - Conference on Local Computer Networks, LCN : 530-531. ScholarBank@NUS Repository. https://doi.org/10.1109/LCN.2008.4664223||Abstract:||In this paper, we introduce a novel end-to-end approach to QoS management with respect to the diagnosis of QoS violations. We first use a set of end-to-end flow traffic statistics to describe a QoS violation. Subsequently, neural network techniques are engaged to identify and differentiate QoS violations through classification of the collected statistics. Through experiments, we find that our scheme outperforms traditional rule-based methods which require clear margins of QoS parameters in asserting a QoS violation. ©2008 IEEE.||Source Title:||Proceedings - Conference on Local Computer Networks, LCN||URI:||http://scholarbank.nus.edu.sg/handle/10635/41847||ISBN:||9781424424139||DOI:||10.1109/LCN.2008.4664223|
|Appears in Collections:||Staff Publications|
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