An ARIMA model for forecasting Wi-Fi data network traffic values

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Auteur principal: Cesar Augusto Hernández Suarez
Format: Artículo científico
Langue:en
Publié: Universidad Nacional de Colombia 2009
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author Cesar Augusto Hernández Suarez
author_facet Cesar Augusto Hernández Suarez
contents An ARIMA model for forecasting Wi-Fi data network traffic values Cesar Augusto Hernández Suarez Octavio José Salcedo Parra Andrés Escobar Díaz Ingeniería data ARIMA network correlation time series This present scientific and technological research was aimed at showing that time series represent an excellent tool for data traffic modelling within Wi-Fi networks. Box-Jenkins methodology (described herein) was used for this purpose. Wi-Fi traffic modelling through correlated models, such as time series, allowed a great part of the data's behaviourl dynamics to be adjusted into a single equation and future traffic values to be estimated based on this. All this is advantageous when it comes to planning integrated coverage, reserving resources and performing more efficient and timely control at different levels of the Wi-Fi data network functional hierarchy. A six order ARIMA traffic model was obtained as a research outcome which predicted traffic with relatively small mean square error values for an 18-day term. 2009 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64311752011 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.29
format Artículo científico
id redalyc_64311752011
institution Redalyc
language en
publishDate 2009
publisher Universidad Nacional de Colombia
spellingShingle An ARIMA model for forecasting Wi-Fi data network traffic values
Cesar Augusto Hernández Suarez
Ingeniería
data
ARIMA
network
correlation
time series
An ARIMA model for forecasting Wi-Fi data network traffic values Cesar Augusto Hernández Suarez Octavio José Salcedo Parra Andrés Escobar Díaz Ingeniería data ARIMA network correlation time series This present scientific and technological research was aimed at showing that time series represent an excellent tool for data traffic modelling within Wi-Fi networks. Box-Jenkins methodology (described herein) was used for this purpose. Wi-Fi traffic modelling through correlated models, such as time series, allowed a great part of the data's behaviourl dynamics to be adjusted into a single equation and future traffic values to be estimated based on this. All this is advantageous when it comes to planning integrated coverage, reserving resources and performing more efficient and timely control at different levels of the Wi-Fi data network functional hierarchy. A six order ARIMA traffic model was obtained as a research outcome which predicted traffic with relatively small mean square error values for an 18-day term. 2009 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64311752011 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.29
title An ARIMA model for forecasting Wi-Fi data network traffic values
topic Ingeniería
data
ARIMA
network
correlation
time series
url https://www.redalyc.org/articulo.oa?id=64311752011