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An ARIMA Based Approach for Traffic Prediction

Published on August 2011 by Sunil Kumar P V
journal_cover_thumbnail

International Conference on Information Systems and Technology
Foundation of Computer Science USA
ICIST - Number 1
August 2011
Authors: Sunil Kumar P V
d22b57ea-3ad5-4f7e-98bc-022e11c1dc00

Sunil Kumar P V . An ARIMA Based Approach for Traffic Prediction. International Conference on Information Systems and Technology. ICIST, 1 (August 2011), 7-10.

@article{
author = { Sunil Kumar P V },
title = { An ARIMA Based Approach for Traffic Prediction },
journal = { International Conference on Information Systems and Technology },
issue_date = { August 2011 },
volume = { ICIST },
number = { 1 },
month = { August },
year = { 2011 },
issn = 0975-8887,
pages = { 7-10 },
numpages = 4,
url = { /proceedings/icist/number1/3261-icist016/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Information Systems and Technology
%A Sunil Kumar P V
%T An ARIMA Based Approach for Traffic Prediction
%J International Conference on Information Systems and Technology
%@ 0975-8887
%V ICIST
%N 1
%P 7-10
%D 2011
%I International Journal of Computer Applications
Abstract

Network traffic prediction plays a vital role in the optimal resource allocation and management in computer networks. This paper introduces an ARIMA based model for the real time prediction of VBR video traffic. The methodology presented here can successfully addresses the challenges in traffic prediction such as accuracy in prediction, resource management and utilization. ARIMA application on a VBR video trace results in a component wise representation of the trace which in turn used for prediction. A brief introduction of the classic prediction scheme of ALP along with a quantitative comparison of the ARIMA with ALP is also presented. Performance evaluation of the proposed method is carried out using RMSE. The prediction accuracy is improved by 23% and the error variance is reduced by 18%.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Traffic prediction ARIMA ALP VBR Video