  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 similar to the process of creating
videos with multiple bit rates in dynamic adaptive streaming over HTTP.
NeuSaver utilizes the commonly used H.264 video codec. We evaluated NeuSaver in
various experiments and a user study through four video categories along with
the state-of-the-art model. Our experiments showed that NeuSaver effectively
reduces the power consumption of mobile devices when streaming video by an
average of 16.14% and up to 23.12% while achieving high QoE.
