Please use this identifier to cite or link to this item: https://doi.org/10.1109/LCN.2008.4664223
Title: End-to-end diagnosis of QoS violations with neural network
Authors: Zhou, L. 
Chen, L. 
Hung, K.P. 
Lek, H.N.
Issue Date: 2008
Source: 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
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