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Behavior Analysis for WebRTC Peer-to-Peer Streaming with Dynamic Topology

Authors:
Khalid Kahloot
Patrik J. Braun
Peter Ekler

Keywords: Correlation; Peer-to-Peer (P2P); State Modeling; Markov chains

Abstract:
Peer-to-Peer (P2P) data streaming in web browsers without the need of a third-party plugin is a preferable privacy-preserving option. However, the complexity of network is a challenge concerning theP2P topology and coding calculations. Despite the performance enhancing added by Web Real-Time Communication (WebRTC) over traditional P2P Communication, protocols overhead produce burst Traffic and the burstiness has a significant impact on the network performance. In this paper, we present a behavior analysis for burstiness and correlation for a WebRTC P2P file steaming. Then, we suggest a model of states like the Markovian chain. We evaluate some of the popular burstiness measures and present different kinds of traffic produced by two protocols WebPeer and CodedWebPeer based on P2P streaming. For modeling, we describe three main stochastic states of the peers regarding their position in the network and their stored data. We aim to contribute to better understanding of the behavior of traffic overhead caused by the protocols in static topology and dynamic joining topology. The results presented in this paper help to design P2P solutions based on WebRTC technologies.

Pages: 35 to 40

Copyright: Copyright (c) IARIA, 2017

Publication date: July 23, 2017

Published in: conference

ISSN: 2308-4219

ISBN: 978-1-61208-572-2

Location: Nice, France

Dates: from July 23, 2017 to July 27, 2017