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This study introduces an environment-aware HTTP adaptive streaming (HAS) scheme. It enhances video Quality of Experience (QoE) for mobile users by considering environmental factors in rate adaptation.

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HTTP adaptive streamingenvironment-awarequality of experiencesensors in mobile phone

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Area of Science:

  • Computer Science
  • Multimedia Systems

Background:

  • HTTP adaptive streaming (HAS) is a dominant internet media streaming method.
  • Current HAS mechanisms enhance Quality of Experience (QoE) but neglect environmental impacts on mobile users.
  • Mobile video consumption occurs in diverse scenarios, necessitating environment-specific QoE evaluation.

Purpose of the Study:

  • To propose an environment-aware HAS scheme that tailors video QoE evaluation to different environments.
  • To develop a model-driven, environment-aware HAS rate adaptation algorithm utilizing mobile phone sensors.

Main Methods:

  • Constructed and validated a video QoE model based on environment perception using mobile phone sensors.
  • Designed a model-driven, environment-aware HAS rate adaptation algorithm.
  • Evaluated the scheme using an environment-aware DASH (Dynamic Adaptive Streaming over HTTP) player in real mobile environments.

Main Results:

  • The proposed scheme provides differentiated rate adaptation suitable for various environments.
  • Experimental results show a higher QoE compared to benchmark HAS mechanisms.
  • Demonstrated the effectiveness of environment-aware rate adaptation in improving mobile video streaming.

Conclusions:

  • Environmental factors significantly influence mobile video QoE.
  • An environment-aware HAS scheme can optimize video streaming performance for mobile users.
  • Integrating environment perception into HAS algorithms is crucial for enhancing mobile video QoE.