논문 ID: 2224.34191

NEMO: enabling neural-enhanced video streaming on commodity mobile devices

Hyunho Yeo, Chan Ju Chong, Youngmok Jung, Juncheol Ye, Dongsu Han

제출 2020-09-21

원문 초록

The demand for mobile video streaming has experienced tremendous growth over the last decade. However, existing methods of video delivery fall short of delivering high-quality video. Recent advances in neural super-resolution have opened up the possibility of enhancing video quality by leveraging client-side computation. Unfortunately, mobile devices cannot benefit from this because it is too expensive in computation and power-hungry. To overcome the limitation, we present NEMO, a system that enables real-time video super-resolution on mobile devices. NEMO applies neural super-resolution to a few select frames and transfers the outputs to benefit the remaining frames. The frames to which super-resolution is applied are carefully chosen to maximize the overall quality gains. NEMO leverages fine-grained dependencies using information from the video codec and strives to provide guarantees in the quality degradation compared to per-frame super-resolution. Our evaluation using a full system implementation on Android shows NEMO improves the overall processing throughput by x11.5, reduces energy consumption by 88.6%, and maintains device temperatures at acceptable levels compared to per-frame super-resolution, while ensuring high video quality. Overall, this leads to a 31.2% improvement in quality of experience for mobile users.

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