Analysis of Model for Multichannel Peer-to-Peer TV Network with View-Upload Decoupling Scheme

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Abstract


In recent years, video streaming systems such as P2PTV successfully use P2P-based networks to allow users watching numerous streaming TV channels. Various designs of an overlaid network were proposed to improve the quality of services of P2PTV. In this paper, we explore View-Upload Decoupling-scheme (VUD), which strictly decouples data to what peer uploads and what it personally views. It’s based on the split of downloaded user data streams into two types: the stream of the chosen TV channel, and the stream (one or more) of the other TV channel, exclusively to deliver it to other users. Such peers form the distribution swarm which is assigned the streams of the channels with low popularity, so that would guarantee the stability of multichannel systems. The mathematical model of VUD scheme is proposed, which considers two classes of users - homogeneous type (all users have the same upload rate) and heterogeneous systems (there are two types of users - with low and high upload rate). We develop the method for calculation the probability of universal streaming - one of the key performance indicators in streaming TV - when all users receive the requested video data with guaranteed quality, defined in the service level agreement (SLA). We propose a method for calculating the probability of universal streaming for a single channel. Statistically significant results for a small network in comparison to VUD and ISO schemes are presented.

About the authors

Yu V Gaidamaka

Peoples’ Friendship University of Russia (RUDN University)

Email: ygaidamaka@sci.pfu.edu.ru
6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
Department of Applied Probability and Informatics

E G Medvedeva

Peoples’ Friendship University of Russia (RUDN University)

Email: egmedvedeva@gmail.com
6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
Department of Applied Probability and Informatics

S I Salpagarov

Peoples’ Friendship University of Russia (RUDN University)

Email: sismalg@gmail.com
6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
Department of Information Technologies

E V Bobrikova

Peoples’ Friendship University of Russia (RUDN University)

Email: ebobrikova@gmail.com
6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
Department of Applied Probability and Informatics

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Copyright (c) 2017 Гайдамака Ю.В., Медведева Е.Г., Салпагаров С.И., Бобрикова Е.В.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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