Affiliation:
1. Hubei University of Economics, and University of Technology Sydney
2. University of Technology Sydney, Broadway, Sydney, Australia
3. Wuhan University, Wuhan, China
4. Hubei University of Economics, Wuhan, China
Abstract
The article presents a novel affective content-aware adaptation scheme (ACAA) to optimize Quality of Experience (QoE) for dynamic adaptive video streaming over HTTP (DASH). Most of the existing DASH adaptation schemes conduct video bit-rate adaptation based on an estimation of available network resources, which ignore user preference on affective content (AC) embedded in video data streaming over the network. Since the personal demands to AC is very different among all viewers, to satisfy individual affective demand is critical to improve the QoE in commercial video services. However, the results of video affective analysis cannot be applied into a current adaptive streaming scheme directly. Correlating the AC distributions in user's viewing history to each being streamed segment, the affective relevancy can be inferred as an affective metric for the AC related segment. Further, we have proposed an ACAA scheme to optimize QoE for user desired affective content while taking into account both network status and affective relevancy. We have implemented the ACAA scheme over a realistic trace-based evaluation and compared its performance in terms of network performance, QoE with that of Probe and Adaptation (PANDA), buffer-based adaptation (BBA), and Model Predictive Control (MPC). Experimental results show that ACAA can preserve available buffer time for future being delivered affective content preferred by viewer's individual preference to achieve better QoE in affective contents than those normal contents while remain the overall QoE to be satisfactory.
Funder
Educational Commission Planning Project of Hubei
National Natural Science Foundation of China
National Key Research and Development Program of China
Natural Science Foundation of Hubei
Wuhan Science and Technology Plan
Key Technological Innovation Projects of Hubei
China Scholarship Council
Humanities and Social Science Project of Ministry of Education
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Hardware and Architecture
Cited by
8 articles.
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