Publikation: Empowerment of Atypical Viewers via Low...
Stammdaten
Titel: | Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video Streaming Quality |
Untertitel: | |
Kurzfassung: | Quality of Experience (QoE) and QoE models are of an increasing importance to networked systems. The traditional QoE modeling for video streaming applications builds a one-size-fits-all QoE model that underserves atypical viewers who perceive QoE differently. To address the problem of atypical viewers, this paper proposes iQoE (individualized QoE), a method that employs explicit, expressible, and actionable feedback from a viewer to construct a personalized QoE model for this viewer. The iterative iQoE design exercises active learning and combines a novel sampler with a modeler. The chief emphasis of our paper is on making iQoE sample-efficient and accurate. By leveraging the Microworkers crowdsourcing platform, we conduct studies with 120 subjects who provide 14,400 individual scores. According to the subjective studies, a session of about 22 minutes empowers a viewer to construct a personalized QoE model that, compared to the best of the 10 baseline models, delivers the average accuracy improvement of at least 42% for all viewers and at least 85% for the atypical viewers. The large-scale simulations based on a new technique of synthetic profiling expand the evaluation scope by exploring iQoE design choices, parameter sensitivity, and generalizability. |
Schlagworte: | video streaming, personalization, quality of experience, modeling, sample efficiency, accuracy, subjective study, perception dataset, personalized QoE model |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 27.11.2023 (Print) |
Erschienen in: |
ACM CoNEXT 2023 Proceedings of the 19th International Conference on emerging Networking EXperiments and Technolgies
ACM CoNEXT 2023 Proceedings of the 19th International Conference on emerging Networking EXperiments and Technolgies
(
ACM Digital Library;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | 1 |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 27 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 27.11.2023 |
ISBN: | - |
ISSN: | - |
Homepage: | https://dl.acm.org/doi/10.1145/3629139 |
Erscheinungsdatum: | 28.11.2023 |
ISBN (e-book): | - |
eISSN: | 2834-5509 |
DOI: | http://dx.doi.org/10.1145/3629139 |
Homepage: | https://dl.acm.org/doi/10.1145/3629139 |
Open Access |
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AutorInnen
Leonardo Peroni (extern) |
Sergey Gorinsky (extern) |
Farzad Tashtarian (intern) |
Christian Timmerer (intern) |
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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Arbeitsgruppen |
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Kooperationen
Organisation | Adresse | ||
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IMDEA Networks Institute
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ES - 28918 Leganés, Madrid |
Forschungsaktivitäten
(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
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Publikationen: | Keine verknüpften Publikationen vorhanden |
Veranstaltungen: | Keine verknüpften Veranstaltung vorhanden |
Vorträge: | Keine verknüpften Vorträge vorhanden |