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A User Study of Netflix Streaming

  • France JacksonEmail author
  • Rahul Amin
  • Yunhui Fu
  • Juan E. Gilbert
  • James Martin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9186)

Abstract

Netflix and Hulu are examples of HTTP-based Adaptive Streaming (HAS). HAS is unique because it attempts to manage the user’s perceived quality by adapting video quality. Current HAS research fails to address whether adaptations actually make a difference? The main challenge in answering this is the lack of consideration for the end user’s perceived quality. The research community is converging on an accepted set of ‘component metrics’ for HAS. However, determining an objective Quality of Experience (QoE) estimate is an open issue. A between-subject user study of Netflix was conducted to shed light on the user’s perception of quality. We found that users prefer to receive lower video quality levels first with marginal improvements made over time. Currently, content providers switch between the highest and lowest level of quality. This paper seeks to explain a better method that led to higher user satisfaction based on Mean opinion score values (MOS).

Keywords

Perceived video quality Internet video streaming HTTP-based adaptive streaming Simulation modeling Home network Video performance assessment User-Experience assessment 

Notes

Acknowledgements

This material is based upon work supported by CableLabs, Inc. Opinions or points of views expressed in this document are those of the authors and do not necessarily reflect the official position of, or a position endorsed by CableLabs, Inc.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • France Jackson
    • 1
    Email author
  • Rahul Amin
    • 2
  • Yunhui Fu
    • 2
  • Juan E. Gilbert
    • 1
  • James Martin
    • 2
  1. 1.CISE DepartmentUniversity of FloridaGainesvilleUSA
  2. 2.School of ComputingClemson UniversityClemsonUSA

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