Publikation: LALISA: Adaptive Bitrate Ladder Optimiz...
Stammdaten
Titel: | LALISA: Adaptive Bitrate Ladder Optimization in HTTP-based Adaptive Live Streaming |
Untertitel: | |
Kurzfassung: | Video content in Live HTTP Adaptive Streaming (HAS) is typically encoded using a pre-defined, fixed set of bitrate-resolution pairs (termed Bitrate Ladder), allowing play-back devices to adapt to changing network conditions using an adaptive bitrate (ABR) algorithm. However, using a fixed one-size-fits-all solution when faced with various content complexities, heterogeneous network conditions, viewer device resolutions and locations, does not result in an overall maximal viewer quality of experience (QoE). Here, we consider these factors and design LALISA, an efficient framework for dynamic bitrate ladder optimization in live HAS. LALISA dynamically changes a live video session’s bitrate ladder, allowing improvements in viewer QoE and savings in encoding, storage, and bandwidth costs. LALISA is independent of ABR algorithms and codecs, and is deployed along the path between viewers and the origin server. In particular, it leverages the latest developments in video analytics to collect statistics from video players, content delivery networks and video encoders, to perform bitrate ladder tuning. We evaluate the performance of LALISA against existing solutions in various video streaming scenarios using a trace-driven testbed. Evaluation results demonstrate significant improvements in encoding computation (24.4%) and bandwidth (18.2%) costs with an acceptable QoE. |
Schlagworte: | Bitrate Ladder, Live Streaming, HTTP Adaptive Streaming, ABR, Optimization, Computation and Bandwidth Costs |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 08.05.2023 (Print) |
Erschienen in: |
NOMS 2023 Proceedings of the IEEE/IFIP Network Operations and Management Symposium
NOMS 2023 Proceedings of the IEEE/IFIP Network Operations and Management Symposium
(
IEEE Xplore Digital Library;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 9 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 08.05.2023 |
ISBN: |
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ISSN: | 2374-9709 |
Homepage: | https://ieeexplore.ieee.org/document/10154347 |
Erscheinungsdatum: | 21.06.2023 |
ISBN (e-book): | - |
eISSN: | - |
DOI: | http://dx.doi.org/10.1109/noms56928.2023.10154347 |
Homepage: | https://ieeexplore.ieee.org/document/10154347 |
Open Access |
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AutorInnen
Farzad Tashtarian (intern) | ||||
Abdelhak Bentaleb
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Hadi Amirpourazarian (intern) | ||||
Babak Taraghi (intern) | ||||
Christian Timmerer (intern) | ||||
Hermann Hellwagner (intern) | ||||
Roger Zimmermann (extern) |
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
Kategorisierung
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Forschungscluster | Kein Forschungscluster ausgewählt |
Peer Reviewed |
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Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
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Kooperationen
Organisation | Adresse | ||
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Concordia University
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CA
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National University of Singapore
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SG - 119077 Singapur |
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(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
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Publikationen: | Keine verknüpften Publikationen vorhanden |
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