Study of QoE for DASH at Sub-representational Level

Dynamic Adaptive Streaming over HTTP has become the most commonly used technology in video streaming. It enables the player to adapt to the bitrate of the video while streaming to ensure continuous playback. DASH provides sub-representation structure that can be extrapolated for refining QoE metric with multiple temporal quality operating point for a given spatial quality i.e. PSNR. In this work we use frame visual significance metric and frame loss induced distortion metric to drive a DASH sub-representational scheme that offers a spatio-temporal QoE tradeoff at a much finer granular scale. By comparing with a typical throughput, segment aware driven DASH under varying network conditions, we demonstrate DASH driven at sub-representational level manages the QoE better under same conditions. This is ideally suited for applications that demand low-delay to prevent playback buffer underflow.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Electrical Engineering (UMKC)

Grantor dc:publisher

University of Missouri--Kansas City

Year dc:date.issued

2017

Author dc:creator

• Swamy, Deepthi Basavapatna Narayana

Advisor dc:contributor.advisor

• Medhi, Deepankar

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/10355/62673

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/62673