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YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis
Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the cont...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192599/ http://dx.doi.org/10.1038/s41597-022-01418-y |
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author | Loh, Frank Wamser, Florian Poignée, Fabian Geißler, Stefan Hoßfeld, Tobias |
author_facet | Loh, Frank Wamser, Florian Poignée, Fabian Geißler, Stefan Hoßfeld, Tobias |
author_sort | Loh, Frank |
collection | PubMed |
description | Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases. |
format | Online Article Text |
id | pubmed-9192599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91925992022-06-15 YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis Loh, Frank Wamser, Florian Poignée, Fabian Geißler, Stefan Hoßfeld, Tobias Sci Data Data Descriptor Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases. Nature Publishing Group UK 2022-06-13 /pmc/articles/PMC9192599/ http://dx.doi.org/10.1038/s41597-022-01418-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Loh, Frank Wamser, Florian Poignée, Fabian Geißler, Stefan Hoßfeld, Tobias YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title | YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title_full | YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title_fullStr | YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title_full_unstemmed | YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title_short | YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis |
title_sort | youtube dataset on mobile streaming for internet traffic modeling and streaming analysis |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192599/ http://dx.doi.org/10.1038/s41597-022-01418-y |
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