Context-aware adaptation of mobile video decoding resolution

TL;DR

This paper introduces a context-aware approach to adapt mobile video decoding resolution, aiming to reduce energy consumption while maintaining user quality expectations by considering user activity, video content, and personality traits.

Contribution

It presents a novel, adaptive method for video resolution adjustment based on context, integrating user behavior and content analysis to optimize energy efficiency.

Findings

Decoding resolution significantly impacts mobile power consumption.

User activity and personality influence acceptable video quality levels.

Context-aware adaptation improves energy savings without compromising user satisfaction.

Abstract

While the evolution of mobile computing is experiencing a considerable growth, it is at the same time seriously threatened by the limitations of the battery technology, which does not keep pace with the evergrowing increase in energy requirements of mobile applications. A novel approach for reducing the energy appetite of mobile apps comes from the approximate computing field, which proposes techniques that in a controlled manner sacrifice computation accuracy for higher energy savings. Building on this philosophy we propose a context-aware mobile video quality adaptation that reduces the energy needed for video playback, while ensuring that a user's quality expectations with respect to the mobile video are met. We confirm that the decoding resolution can play a significant role in reducing the overall power consumption of a mobile device and conduct two user studies to investigate how the context in which a video is played, its content, and the user's personality, modulate a user's quality expectations. We discover that a user's physical activity, the spatial/temporal properties of the video, and the user's personality traits interact and jointly influence the minimal acceptable playback resolution, paving the way for context-adaptable approximate mobile computing.