Ensemble classifier for traffic in presence of changing distributions

Wang, Runxin and Shi, Lei and Jennings, Brendan (2013) Ensemble classifier for traffic in presence of changing distributions. In: 2013 IEEE Symposium on Computers and Communications, ISCC 2013 :. Proceedings - International Symposium on Computers and Communications . Institute of Electrical and Electronics Engineers Inc., HRV, pp. 629-635. ISBN 9781479937554

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Traffic classification plays an important role in many short to medium term network management tasks and in long term network dimensioning/planning. In recent years a number of traffic classifiers have been proposed, in particular classifiers based on machine learning techniques exhibit high levels of accuracy. However, in practice, even if classifiers can be accurately trained at a given time, their accuracy will subsequently degrade when the characteristics of the network traffic change. In this paper, we propose an adjustable traffic classification system, the key technique of which is ensemble classification, assisted with a change detection method. Our system enables a traffic classifier to be effectively updated in response to the changing traffic distributions. Experimental results show that our classifier produces improved accuracy with relatively shorter updating time.

Item Type: Book Section
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1700/1712
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Depositing User: Admin SSL
Date Deposited: 19 Oct 2022 23:15
Last Modified: 07 Jun 2023 18:38
URI: http://repository-testing.wit.ie/id/eprint/4958

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