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H.264 and H.265 Video Bandwidth Prediction
Journal article   Peer reviewed

H.264 and H.265 Video Bandwidth Prediction

A. Kalampogia and P. Koutsakis
IEEE Transactions on Multimedia, Vol.20(1), pp.171-182
2018
DOI: https://doi.org/10.1109/TMM.2017.2713642
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Abstract

The explosive growth of multimedia applications renders the efficiency of network resource allocation a problem of major importance. The burstiness of video traffic, in particular, calls for traffic control solutions that will help prevent significant packet losses. Such losses can lead to unacceptable quality of service (QoS) and quality of experience (QoE) to users. In this paper, we focus on a large variety of H.264- and H.265-encoded video traces with different GoP patterns. Different versions of each trace, in low, medium, and high quality have been used in our study. We evaluate the accuracy of an existing video traffic prediction approach for the size of B-frames, and we propose a new Markovian model that predicts B-frames’ sizes with significantly higher accuracy. B-frame size prediction can be used in order to reduce bandwidth requirements and smooth the encoded video stream, by selective B-frame dropping, when the model predicts larger upcoming B-frame traffic than the network can handle.

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32 Record Views
21 Times Cited - Web of Science

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Collaboration types
Domestic collaboration
International collaboration
Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.101 Security, Encryption & Encoding
4.101.178 Video Coding
Web Of Science research areas
Computer Science, Information Systems
Computer Science, Software Engineering
Telecommunications
ESI research areas
Computer Science
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