Sarigiannidis, P., Aproikidis, K., Louta, M. et al. (2 more authors) (2014) Predicting Multimedia Traffic in Wireless Networks: A Performance Evaluation of Cognitive Techniques. In: The 5th International Conference on Information, Intelligence, Systems and Applications, IISA 2014. IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications, 07-09 Jul 2014, Chania, Greece. IEEE ISBN 978-1-4799-6171-9
Abstract
Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper subsequently published in Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | extrapolation; automata; markov chains; prediction; wireless networks |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > International Faculty (Sheffield) > City College - Computer Science |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 May 2017 14:01 |
Last Modified: | 19 Dec 2022 13:35 |
Published Version: | https://doi.org/10.1109/IISA.2014.6878802 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IISA.2014.6878802 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116429 |