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Robust QoE-aware prediction-based dynamic content adaptation framework applied to slides documents in mobile Web conferencing

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Abstract

In mobile Web conferencing, enterprise documents are generally adapted into JPEG-based Web pages to be visualized on mobile devices. Dynamically identifying the optimal adapted content is very challenging, as a compromise between high visual quality and small delivery time must be made. In this paper, we propose a robust prediction-based dynamic content adaptation framework for JPEG and XHTML formats that computes near-optimal transcoding parameters dynamically with very few computations. The proposed framework is comprised of five methods making different compromises between computational complexity and accuracy. For JPEG, the average deviation from optimality (exhaustive method) is 6 % and 3 % respectively for two of the proposed methods. For XHTML, the average deviation from optimality is 3 % and 1 % respectively using the same two methods. Moreover, the methods reached optimality 30 % and 59 % of the time on the tested documents for JPEG and XHTML respectively, which makes the proposed framework very appealing.

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Author information

Authors and Affiliations

  1. Synchromedia Laboratory for Multimedia Communication in Telepresence, École de Technologie Supérieure, Université du Québec, Montreal, Canada

    Habib Louafi

  2. Department of Software and IT Engineering, École de Technologie Supérieure, Université du Québec, Montreal, Canada

    Stéphane Coulombe

  3. Nokia Research Center, Palo Alto, CA, USA

    Umesh Chandra

Authors
  1. Habib Louafi
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  2. Stéphane Coulombe
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  3. Umesh Chandra
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Correspondence to Habib Louafi.

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Louafi, H., Coulombe, S. & Chandra, U. Robust QoE-aware prediction-based dynamic content adaptation framework applied to slides documents in mobile Web conferencing. Multimed Tools Appl 74, 7883–7920 (2015). https://doi.org/10.1007/s11042-014-2030-2

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  • DOI: https://doi.org/10.1007/s11042-014-2030-2

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