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A proposal based on time series to predict traffic values inside a Wi-Fi data network

Published: 14 December 2009 Publication History

Abstract

This work aimed to show that time series are an excellent tool for data traffic modelling within Wi-Fi networks. Box-Jenkins methodology, which is herein described, was used to achieve this objective.
Wi-Fi traffic modelling through correlated models, like time series, allow to adjust a great part of the data behavior dynamics in a single equation and, based on it, to estimate traffic future values. All this is advantageous when it comes to covering planning and resource reservation as well as performing a more efficient and timely control at different levels of the Wi-Fi data network functional hierarchy.
An 18-order ARIMA traffic model was obtained as a research outcome, which predicted the traffic with relatively small mean square error values for a 10-day term.

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cover image ACM Other conferences
MoMM '09: Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
December 2009
663 pages
ISBN:9781605586595
DOI:10.1145/1821748
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Johannes Kepler University

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Association for Computing Machinery

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Publication History

Published: 14 December 2009

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Author Tags

  1. ARIMA
  2. communication network
  3. correlation
  4. time series
  5. traffic model

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