DocumentCode :
640434
Title :
Lightweight resource estimation model to extend battery life in video playback
Author :
Rintaluoma, Tero ; Silven, Olli
Author_Institution :
Google, Oulu, Finland
fYear :
2013
fDate :
15-18 July 2013
Firstpage :
96
Lastpage :
103
Abstract :
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 effectively 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.
Keywords :
mobile computing; multimedia systems; power aware computing; battery life extension; frequency scaling scheme; lightweight resource estimation model; mobile computing devices; multimedia signal processing; video playback time; voltage scaling scheme; Clocks; Complexity theory; Decoding; Estimation; Mathematical model; Resource management; Streaming media;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS XIII), 2013 International Conference on
Conference_Location :
Agios Konstantinos
Type :
conf
DOI :
10.1109/SAMOS.2013.6621111
Filename :
6621111
Link To Document :
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