Please use this identifier to cite or link to this item:
https://doi.org/10.1109/LCN.2008.4664223
DC Field | Value | |
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dc.title | End-to-end diagnosis of QoS violations with neural network | |
dc.contributor.author | Zhou, L. | |
dc.contributor.author | Chen, L. | |
dc.contributor.author | Hung, K.P. | |
dc.contributor.author | Lek, H.N. | |
dc.date.accessioned | 2013-07-04T08:37:15Z | |
dc.date.available | 2013-07-04T08:37:15Z | |
dc.date.issued | 2008 | |
dc.identifier.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 | |
dc.identifier.isbn | 9781424424139 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/41847 | |
dc.description.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. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/LCN.2008.4664223 | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTATIONAL SCIENCE | |
dc.description.doi | 10.1109/LCN.2008.4664223 | |
dc.description.sourcetitle | Proceedings - Conference on Local Computer Networks, LCN | |
dc.description.page | 530-531 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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