基于对端连接统计的实时视频流性能预测

2015 IEEE 3rd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) Pub Date : 2015-11-01 DOI:10.1109/AIEEE.2015.7367314

Julius Skirelis, A. Serackis

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引用次数: 1

摘要

本文研究的目的是设计一个视频流性能预测器，用于自适应视频流应用。本文对基于神经网络的预测器进行了分析。为了在动态变化的移动数据吞吐量条件下记录的真实WebRTC统计数据上测试经过训练的预测器，进行了实验研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Prediction of the real-time video streaming performance based on the peer connection statistics

The aim of the investigation presented in this paper was to design a video stream performance predictor, which could be used for adaptive video streaming applications. The neural networks based predictors were analyzed in this paper. An experimental investigation was performed in order to test the once trained predictors on a real WebRTC statistical data, recorded in dynamically changing mobile data throughput conditions.

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来源期刊

2015 IEEE 3rd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)

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