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An ARIMA model for forecasting Wi-Fi data network traffic values
Modelo ARIMA para pronosticar valores de tráfico en una red de datos Wi-Fi
DOI:
https://doi.org/10.15446/ing.investig.v29n2.15163Keywords:
ARIMA, correlation, data-network, traffic model, time series (en)ARIMA, correlación, modelo de tráfico, red de datos, serie de tiempo (es)
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 behavioral 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.
El presente artículo de investigación científica y tecnológica tiene por objetivo demostrar que las series de tiempo son una excelente herramienta para el modelamiento de tráfico de datos en redes Wi-Fi. Para lograr este objetivo se utilizó la metodología de Box-Jenkins, la cual se describe. El modelamiento de tráfico Wi-Fi a través de modelos correlacionados como las series de tiempo, permiten ajustar gran parte de la dinámica del comportamiento de los datos en una ecuación y con base en esto estimar valores futuros de tráfico. Lo anterior es una ventaja para la planeación de cobertura, reservación de recursos y la realización de un control más oportuno y eficiente en forma integrada a diferentes niveles de la jerarquía funcional de la red de datos Wi-Fi. Como resultado de la investigación se obtuvo un modelo de tráfico ARIMA de orden 6, el cual realizó pronósticos de tráfico con valores del error cuadrático medio relativamente pequeños, para un periodo de 18 días.
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Copyright (c) 2009 Cesar Augusto Hernández Suarez, Octavio José Salcedo Parra, Andrés Escobar Díaz
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