NeuSaver: Neural Adaptive Power Consumption Optimization for Mobile Video Streaming
Kyoungjun Park, Myungchul Kim, Laihyuk Park

TL;DR
NeuSaver is a reinforcement learning-based system that adaptively adjusts video frame rates during streaming to significantly reduce mobile device power consumption without degrading user experience.
Contribution
It introduces a novel RL-based adaptive frame rate policy for mobile video streaming that optimizes power savings while maintaining QoE.
Findings
Reduces mobile video streaming power consumption by up to 23.12%.
Achieves an average power reduction of 16.14%.
Maintains high QoE comparable to non-adaptive streaming.
Abstract
Video streaming services strive to support high-quality videos at higher resolutions and frame rates to improve the quality of experience (QoE). However, high-quality videos consume considerable amounts of energy on mobile devices. This paper proposes NeuSaver, which reduces the power consumption of mobile devices when streaming videos by applying an adaptive frame rate to each video chunk without compromising user experience. NeuSaver generates an optimal policy that determines the appropriate frame rate for each video chunk using reinforcement learning (RL). The RL model automatically learns the policy that maximizes the QoE goals based on previous observations. NeuSaver also uses an asynchronous advantage actor-critic algorithm to reinforce the RL model quickly and robustly. Streaming servers that support NeuSaver preprocesses videos into segments with various frame rates, which is…
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Taxonomy
TopicsImage and Video Quality Assessment · Caching and Content Delivery · Video Coding and Compression Technologies
