Forecasting network activities using ARIMA method

H. Haviluddin, R. Alfred
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引用次数: 27

Abstract

This paper presents an approach for a network traffic characterization by using an ARIMA (Autoregressive Integrated Moving Average) technique. The dataset used in this study is obtained from the internet network traffic activities of the Mulawarman University for a period of a week. The results are obtained using the Box-Jenkins Methodology. The Box-Jenkins methodology consists of five ARIMA models which include ARIMA (2, 1, 1) (1, 1, 1) ¹², ARIMA (1, 1, 1) (1, 1, 1) ¹², ARIMA (2, 1, 0) (1, 1, 1) ¹², ARIMA (0, 1, 0) (1, 1, 1) ¹², and ARIMA (0, 1, 0) (1, 2, 1) ¹². In this paper, ARIMA (0, 1, 0) (1, 2, 1) ¹² was selected as the best model that can be used to model the internet network traffic.
使用ARIMA方法预测网络活动
本文提出了一种利用ARIMA(自回归综合移动平均)技术表征网络流量的方法。本研究使用的数据集来自Mulawarman大学为期一周的互联网网络流量活动。使用Box-Jenkins方法获得结果。Box-Jenkins方法包括五个ARIMA模型包括ARIMA(2, 1, 1)(1, 1, 1)¹²,ARIMA(1, 1, 1)(1, 1, 1)¹²,ARIMA(2 1 0)(1, 1, 1)¹²,ARIMA(0,1,0)(1, 1, 1)¹²,,ARIMA(0,1,0)(1、2、1)¹²。本文选择ARIMA (0,1,0) (1,2,1) ¹²作为可用于互联网网络流量建模的最佳模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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