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
Link To Document