Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/6208
Title: A modular sampling framework for flexible traffic analysis
Authors: João Marco
Carvalho,P
Lima,SR
Issue Date: 2015
Abstract: The paradigm of having everyone and everything connected in an ubiquitous way poses huge challenges to today's networks due to the massive traffic volumes involved. To turn treatable all network tasks requiring traffic analysis, sampling the traffic has become mandatory triggering substantial research in the area. Aiming at fostering the deployment and tuning of new sampling techniques, this paper presents a flexible sampling framework developed following a multilayer design in order to easily set up the characteristics of a sampling technique according to the measurement task to be assisted. The framework implementation relies on a comprehensive sampling taxonomy which identifies the granularity, selection scheme and selection trigger as the inner characteristics distinguishing current sampling proposals. As proof of concept of the versatility of this framework in testing the suitability of distinct sampling schemes, this work provides a comparative performance evaluation of classical and recent sampling techniques regarding the estimation accuracy, the volume of data involved in the sampling process and the computational weight in terms of CPU and memory usage. © 2015 University of Split, FESB.
URI: http://repositorio.inesctec.pt/handle/123456789/6208
http://dx.doi.org/10.1109/softcom.2015.7314061
metadata.dc.type: conferenceObject
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Appears in Collections:Non INESC TEC publications - Articles in International Conferences

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