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Performance analytics of a virtual reality streaming model
Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.ORCID iD: 0000-0001-8929-4911
2020 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) / [ed] Hermanns H., Springer , 2020, Vol. 12040, p. 1-18Conference paper, Published paper (Refereed)
Abstract [en]

This work focuses on post-analysis of performance results by means of Performance Analytics. The results to be post-analysed are provided by a Stochastic Fluid Flow Model (SFFM) of Virtual Reality (VR) streaming. Performance Analytics implies using the Machine Learning (ML) algorithm M5P for constructing model trees, which we examine amongst others for asymptotic behaviours and parameter impacts in both uni- and multivariate settings. We gain valuable insights into key parameters and related thresholds of importance for good VR streaming performance. © Springer Nature Switzerland AG 2020.

Place, publisher, year, edition, pages
Springer , 2020. Vol. 12040, p. 1-18
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 03029743
Keywords [en]
Asymptotic behaviour, M5P algorithm, Machine Learning, Multivariate analysis, Stochastic Fluid Flow Model, Asymptotic analysis, Flow of fluids, Learning algorithms, Learning systems, Multivariant analysis, Stochastic models, Stochastic systems, Trees (mathematics), Virtual reality, Constructing models, Fluid flow modeling, Multi variate analysis, Parameter impacts, Post analysis, Streaming model
National Category
Production Engineering, Human Work Science and Ergonomics Computer Sciences
Identifiers
URN: urn:nbn:se:bth-19369DOI: 10.1007/978-3-030-43024-5_1Scopus ID: 2-s2.0-85082331489ISBN: 9783030430238 OAI: oai:DiVA.org:bth-19369DiVA, id: diva2:1422840
Conference
20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems, MMB 2020; Saarbrücken; Germany; 16 March 2020 through 18 March 2020
Part of project
VIATECH- Human-Centered Computing for Novel Visual and Interactive Applications, Knowledge Foundation
Funder
Knowledge Foundation, 20170056Available from: 2020-04-09 Created: 2020-04-09 Last updated: 2021-05-04Bibliographically approved

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Fiedler, Markus

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CiteExportLink to record
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Citation style
  • apa
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Language
  • de-DE
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Output format
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