Lightweight Resource Estimation Model to Extend Battery Life in Video Playback

被引:0
|
作者
Rintaluoma, Tero [1 ]
Silven, Olli [2 ]
机构
[1] Google, Kiviharjunlenkki 1 B, Oulu 90220, Finland
[2] Univ Oulu, Dept Comp Sci & Engn, SF-90100 Oulu, Finland
来源
2013 INTERNATIONAL CONFERENCE ON EMBEDDED COMPUTER SYSTEMS: ARCHITECTURES, MODELING AND SIMULATION (IC-SAMOS) | 2013年
关键词
PREDICTION; QUALITY;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Modern mobile computing devices are integrating more and more processing units into a single platform. For this reason separate resource managers are needed to control computing resources efectively and in an energy efficient way. Multimedia signal processing applications, such as a video playback, have huge variations in their resource needs depending on the input sequence characteristics. To improve this situation a resource usage estimation model has been developed and evaluated. By using the model it is possible to estimate the resource needs with less than 10% error marginal on average. A proper exploitation of prior information improves both the user experience and the battery life. On the testing platform already a single step in the dynamic voltage and frequency scaling scheme corresponds to 30 minutes in high definition video playback time. The approach does not require changes to the existing encoders or decoders.
引用
收藏
页码:96 / 103
页数:8
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