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Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Yumin Jo1, Jongho Paik2,*

1 Major in Software Fusion, Department of Computer, Seoul Women’s University, Seoul, 01797, South Korea
2 Department of Software Convergence, Seoul Women’s University, Seoul, 01797, South Korea

* Corresponding Author: Jongho Paik. Email: email

(This article belongs to the Special Issue: Intelligent Computing Techniques and Their Real Life Applications)

Computers, Materials & Continua 2024, 78(3), 4153-4176. https://doi.org/10.32604/cmc.2024.047046

Abstract

Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors, is required. In this paper, we propose an intelligent packet switching method based on the ML method of classification, which is one of the supervised learning methods, that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data. Furthermore, we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them. The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs. In the broadcasting gateway equipment to which the proposed method is applied, it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.

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APA Style
Jo, Y., Paik, J. (2024). Machine-learning based packet switching method for providing stable high-quality video streaming in multi-stream transmission. Computers, Materials & Continua, 78(3), 4153-4176. https://doi.org/10.32604/cmc.2024.047046
Vancouver Style
Jo Y, Paik J. Machine-learning based packet switching method for providing stable high-quality video streaming in multi-stream transmission. Comput Mater Contin. 2024;78(3):4153-4176 https://doi.org/10.32604/cmc.2024.047046
IEEE Style
Y. Jo and J. Paik, “Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission,” Comput. Mater. Contin., vol. 78, no. 3, pp. 4153-4176, 2024. https://doi.org/10.32604/cmc.2024.047046



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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