English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

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 27 % , compared with a processor running at full speed.

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