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A Study on the Quality Monitoring and Prediction of OTT Traffic in ISP
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ISP의 OTT 트래픽 품질모니터링과 예측에 관한 연구

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Type
Academic journal
Author
Chang-Sup Nam (호서대학교)
Journal
Korea Information Electron Communication Technology Journal of Korea Institute of Information, Electronics, and Communication Technology Vol.14 No.2 KCI Accredited Journals
Published
2021.4
Pages
115 - 121 (7page)

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A Study on the Quality Monitoring and Prediction of OTT Traffic in ISP
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This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.
#artificial intelligence #big data #internet quality monitoring #internet traffic #Internet traffic prediction #Machine learning #network traffic

Contents

요약
Abstract
1. 서론
2. 선행연구
3. 트래픽 수집환경 구축
4. 트래픽 모니터링
5. OTT 트래픽 예측
6. 결론
REFERENCES

References (13)

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Tikunov, D. / 2007 / Traffic Pred iction for Mobile Network using Holt-Winte r’s Exponential Smoothing / Telecommunicat ions and Computer Networks, 15th Internati onal Conference :1~5 google schola H. NIE / 2012 / Hybrid of ARIMA and SVMs f or Short-Term Load Forecasting / Internatio nal Conference on Future Energy, Environm ent, and Materials :1455~1460 google schola Shu, Y / 2005 / Wireless traffic modeling and prediction using seasonal ARIMA models / IEICE-transa ctions on Communications 10:3992~3999 google schola L. R. Medsker / 2001 / Recurrent Neural N etwork; Design and Applications :12~14 google schola Luis G. B. R. / 2016 / An Application of No n-Linear Autoregressive Neural Networks to Predict Energy Consumption in Public Buildings / energies 9(9):684 google schola

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