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A First Look at Adaptive Video Streaming over Multipath QUIC with Shared Bottleneck Detection
Federal University of São Paulo, Brazil.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). Red Hat AB.ORCID iD: 0000-0002-0722-2656
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7311-9334
University of Oslo, Norway.
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2023 (English)In: Proceedings of the 14th ACM Multimedia Systems Conference / [ed] Shervin Shirmohammadi, Mohamed Hefeeda , Roger Zimmermann, Carsten Griwodz, Mea Wang, Association for Computing Machinery (ACM), 2023, p. 161-172Conference paper, Published paper (Refereed)
Abstract [en]

The promises of multipath transport is to aggregate bandwidth and improve resource utilisation and reliability. We demonstrate in this paper that the way multipath coupled congestion control is defined today RFC6359 leads to a sub-optimal resource utilisation when network paths are mainly disjoint, i.e., they do not share a bottleneck. With growing interest to standardise Multipath QUIC (MPQUIC), we implement the practical shared bottleneck detection (SBD) algorithm from RFC8382 in MPQUIC, namely MPQUIC-SBD. We evaluate MPQUIC-SBD through extensive emulation experiments in the context of video streaming. We show that MPQUIC-SBD is able to correctly detect shared bottlenecks over 90% of the time as the video segments’ size increase depending on the Adaptive Bitrate (ABR) algorithm. In non-shared bottleneck scenarios, MPQUIC-SBD results in video throughput gains of more than 13% compared to MPQUIC, which directly translates into better video quality metrics.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2023. p. 161-172
Keywords [en]
Traffic congestion; Bottleneck detection; Congestion control; DASH; First look; Multipath; Multipath QUIC; Multipath transport; QUIC; Resources utilizations; Shared bottleneck detection; Video streaming
National Category
Computer Sciences Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-96260DOI: 10.1145/3587819.3590982Scopus ID: 2-s2.0-85163575009OAI: oai:DiVA.org:kau-96260DiVA, id: diva2:1786458
Conference
14th ACM Multimedia Systems Conference, MMSys 2023, Vancouver, Canada, June 7-10, 2023.
Available from: 2023-08-09 Created: 2023-08-09 Last updated: 2023-08-10Bibliographically approved

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Ferlin, SimoneBrunstrom, Anna

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Citation style
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