Multiple Objective Optimization for Video Streaming (2007)
Abstract / truncated to 115 words
In this thesis, we propose Multiple Objective Optimization (MOO) frameworks for efficient video streaming. Firstly, we introduce pre-roll delay-distortion optimization (DDO) for uninterrupted content-adaptive video streaming over low capacity, constant bitrate (CBR) channels using MOO. Content analysis is used to divide the input video into shots with assigned relevance levels. The video is adaptively encoded and streamed aiming minimum pre-roll delay and distortion with the optimal spatial and temporal resolutions and quantization parameters for each shot. With buffer and distortion constraints, the bitrate of unimportant shots is reduced to achieve an acceptable quality in important shots. Secondly, we introduce a cross-layer optimized video rate adaptation and scheduling scheme to achieve maximum "application layer" Quality-of-Service (QoS), ... toggle 4 keywordscross-layer optimization – video streaming – multiple object optimization – quality of service
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