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Mobile Information Systems
Volume 2016, Article ID 1042525, 10 pages
Research Article

A Dynamic Programming Solution for Energy-Optimal Video Playback on Mobile Devices

School of Computer and Information Engineering, Inha University, Incheon 22212, Republic of Korea

Received 28 December 2015; Revised 8 April 2016; Accepted 11 April 2016

Academic Editor: Wenyao Xu

Copyright © 2016 Minseok Song and Jinhan Park. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Due to the development of mobile technology and wide availability of smartphones, the Internet of Things (IoT) starts to handle high volumes of video data to facilitate multimedia-based services, which requires energy-efficient video playback. In video playback, frames have to be decoded and rendered at high playback rate, increasing the computation cost on the CPU. To save the CPU power, dynamic voltage and frequency scaling (DVFS) dynamically adjusts the operating voltage of the processor along with frequency, in which appropriate selection of frequency on power could achieve a balance between performance and power. We present a decoding model that allows buffering frames to let the CPU run at low frequency and then propose an algorithm that determines the CPU frequency needed to decode each frame in a video, with the aim of minimizing power consumption while meeting buffer size and deadline constraints, using a dynamic programming technique. We finally extend this algorithm to optimize CPU frequencies over a short sequence of frames, producing a practical method of reducing the energy required for video decoding. Experimental results show a system-wide reduction in energy of , compared with a processor running at full speed.