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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

Performance Analytics of a Virtual Reality Streaming Model

verfasst von : Markus Fiedler

Erschienen in: Measurement, Modelling and Evaluation of Computing Systems

Verlag: Springer International Publishing

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Abstract

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.

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Nächstes Kapitel To Fail or Not to Fail: Predicting Hard Disk Drive Failure Time Windows
Fußnoten
1
RP is a typical notion in the fluid context, and not to be confused with a deterministic discrete arrival process, denoted by D in Kendall notation.
 
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Metadaten
Titel
Performance Analytics of a Virtual Reality Streaming Model
verfasst von
Markus Fiedler
Copyright-Jahr
2020
Buch
Measurement, Modelling and Evaluation of Computing Systems

Print ISBN: 978-3-030-43023-8

Electronic ISBN: 978-3-030-43024-5

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-43024-5_1

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