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Performance Analytics of a Virtual Reality Streaming Model

  • Markus FiedlerEmail author
Conference paper
  • 61 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12040)

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.

Keywords

Machine Learning M5P algorithm Stochastic Fluid Flow Model Asymptotic behaviour Multivariate analysis 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Technology and AestheticsBlekinge Institute of TechnologyKarlshamnSweden

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