• DocumentCode
    3719861
  • Title

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

  • Author

    Julius Skirelis;Art?ras Serackis

  • Author_Institution
    Department of Electronic Systems, Vilnius Gediminas Technical University, Naugarduko g. 41-426, LT-03227, Lithuania
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    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.
  • Keywords
    "Streaming media","Training","Neurons","Delays","Biological neural networks","Mobile communication","WebRTC"
  • Publisher
    ieee
  • Conference_Titel
    Information, Electronic and Electrical Engineering (AIEEE), 2015 IEEE 3rd Workshop on Advances in
  • Type

    conf

  • DOI
    10.1109/AIEEE.2015.7367314
  • Filename
    7367314