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Dissecting the performance of YouTube video streaming in mobile networks
Author(s) -
Schwind Anika,
Midoglu Cise,
Alay Özgü,
Griwodz Carsten,
Wamser Florian
Publication year - 2019
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.2058
Subject(s) - computer science , protocol stack , quality of experience , computer network , application layer , real time streaming protocol , the internet , internet traffic , mobile broadband , software deployment , multimedia , quality of service , telecommunications , world wide web , wireless , wireless sensor network , operating system
Summary Video streaming applications constitute a significant portion of the Internet traffic today, with mobile accounting for more than half of the online video views. The high share of video in the current Internet traffic mix has prompted many studies that examine video streaming through measurements. However, streaming performance depends on many different factors at different layers of the TCP/IP stack. For example, browser selection at the application layer or the choice of protocol in transport layer can have significant impact on the video performance. Furthermore, video performance heavily depends on the underlying network conditions (eg, network and link layers). For mobile networks, the conditions vary significantly, since each operator has a different deployment strategy and configuration. In this paper, we focus on YouTube and carry out a comprehensive study investigating the influence of different factors on streaming performance. Leveraging the Measuring Mobile Broadband Networks in Europe (MONROE) test bed that enables experimentation with 13 different network configurations in four countries, we collect more than 1800 measurement samples in operational mobile networks. With this campaign, our goal is to quantify the impact of parameters from different layers on YouTube's streaming quality of experience (QoE). More specifically, we analyze the role of the browser (eg, Firefox and Chrome), the impact of transport protocol (eg, TCP or QUIC), the influence of network bandwidth, and signal coverage on streaming QoE. Our analysis reveals that all these parameters need to be taken into account jointly for network management practices, in order to ensure a high end‐user experience.