Learning Algorithm of Dynamic Threshold in Line Utilization based SARIMA model 


Vol. 9,  No. 6, pp. 841-846, Dec.  2002
10.3745/KIPSTC.2002.9.6.841


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  Abstract

We applies a seasonal ARIMA model to the timely forecasting in a line utilization and its confidence interval on the base of the past data of the line utilization that QoS of the network is greatly influenced by. And this paper proposes the learning algorithm of dynamic threshold in line utilization using the SARIMA model. We can find the proper dynamic threshold in timely line utilization on the various network environments and provide the confidence based on probability. Also, we have evaluated the validity of the proposed model and estimated the value of a proper threshold on real network. Network manager can overcome a shortcoming of original threshold method and maximize the performance of this algorithm.

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[IEEE Style]

K. H. Cho, S. J. Ahn, J. W. Chung, "Learning Algorithm of Dynamic Threshold in Line Utilization based SARIMA model," The KIPS Transactions:PartC, vol. 9, no. 6, pp. 841-846, 2002. DOI: 10.3745/KIPSTC.2002.9.6.841.

[ACM Style]

Kang Hong Cho, Seong Jin Ahn, and Jin Wook Chung. 2002. Learning Algorithm of Dynamic Threshold in Line Utilization based SARIMA model. The KIPS Transactions:PartC, 9, 6, (2002), 841-846. DOI: 10.3745/KIPSTC.2002.9.6.841.

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