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Multimedia Tools and Applications

, Volume 78, Issue 12, pp 15839–15859 | Cite as

The study of new features for video traffic classification

  • Ling-Yun YangEmail author
  • Yu-Ning Dong
  • Wei Tian
  • Zai-Jian Wang
Article
  • 104 Downloads

Abstract

Network traffic classification is important for the management of network resource and the support quality of multimedia services. To realize the fine-grained classification of typical Internet video traffic, this paper studies and analyses the characteristics of video flow change in transmission process and the statistic characteristics of its main protocol data. According to different service models from the network services and the users’ demand of video quality, we propose two new sets of features for video traffic classification, including: downlink rate probability distribution model and main protocol data statistics. The experimental results show that the two sets of features can improve the performance of classification compared to existing methods.

Keywords

Video feature Traffic classification Probability distribution Feature mining 

Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (No.61271233, 61401004, 61601005), the Ph.D Programs Foundation of Anhui Normal university (No. 2016XJJ129), Plan of introduction and cultivation of university leading talents in Anhui (No.gxfxZD2016013).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Communication and Information EngineeringNanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.College of Physics and Electronic InformationAnhui Normal UniversityWuhuChina

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