计算机工程与应用 ›› 2017, Vol. 53 ›› Issue (15): 18-24.DOI: 10.3778/j.issn.1002-8331.1704-0394

• 热点与综述 • 上一篇    下一篇

移动网络YouTube视频码率及分辨率识别方法

林高全1，潘吴斌2，3，程  光2，3，徐  健2，3   

  1. 1.华为技术有限公司 无线产品线，广东 深圳 518129
    2.东南大学 计算机科学与工程学院，南京 210096
    3.计算机网络和信息集成教育部重点实验室（东南大学），南京 210096
  • 出版日期:2017-08-01 发布日期:2017-08-14

Method for YouTube bitrate and resolution identification in mobile networks

LIN Gaoquan1, PAN Wubin2, 3, CHENG Guang2, 3, XU Jian2, 3   

  1. 1.Wireless Product Lines, Huawei Technologies Co. Ltd., Shenzhen, Guangdong 518129, China
    2.School of Computer Science and Engineering, Southeast University, Nanjing 210096, China
    3.Key Laboratory of Computer Network and Information Integration（Southeast University）, Ministry of Education, Nanjing 210096, China
  • Online:2017-08-01 Published:2017-08-14

PDF

摘要： YouTube作为世界最大的视频网站，在网络流量中的占比日益增加。大量的视频流量给互联网服务提供商带来了巨大的挑战。随着YouTube全站采用HTTPS加密，如何从HTTPS加密流量中获取视频QoE评估信息至关重要。在分析了YouTube App在Android和IOS平台上所采用的流媒体传输模式的基础上，提出了C4.5决策树与[K]-means聚类相结合的方法对视频片段进行分辨率识别。实验结果证明该方法能够准确地识别视频播放过程中每个视频片段的播放码率及分辨率。

关键词: YouTube视频, HTTPS加密, ACK Number, 码率识别, 分辨率识别

Abstract: YouTube as the world’s largest video provider, the proportion of video traffic in network traffic is increasing. A lot of video traffic has brought great challenges to the Internet service provider. With the encryption of YouTube traffic, it is important to get video QoE evaluation information from HTTPS encrypted traffic. Based on the analysis of the streaming media transmission mode adopted by YouTube App on Android and IOS platform, this paper proposes a combination of C4.5 decision tree and [k]-means clustering to carry out resolution identification of all the video chunks when users watch the videos. The experimental results show that the method can accurately identify the bitrate and resolution of each video chunk in the video playback process.

Key words: YouTube, HTTPS, ACK Number, bitrate identification, resolution identification

京ICP备13024262号-1
Copyright © 《计算机工程与应用》编辑部
技术支持：北京玛格泰克科技发展有限公司
总访问量
今日访问
在线人数