Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices
This paper investigates the problem of minimizing energy consumption for real-time video encoding on mobile devices, by dynamically configuring the clock frequency in the CPU via the dynamic voltage scaling (DVS) technology. The problem can be formulated as a constrained optimization problem, whose...
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sg-ntu-dr.10356-985442020-05-28T07:17:36Z Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices Yang, Ming Wen, Yonggang Cai, Jianfei Foh, Chuan Heng School of Computer Engineering IEEE International Conference on Communications (2012 : Ottawa, Canada) DRNTU::Engineering::Computer science and engineering This paper investigates the problem of minimizing energy consumption for real-time video encoding on mobile devices, by dynamically configuring the clock frequency in the CPU via the dynamic voltage scaling (DVS) technology. The problem can be formulated as a constrained optimization problem, whose objective is to minimize the total energy consumption of encoding video contents while respecting a real-time delay constraint. Under a probabilistic workload model, we obtain closed-form solutions for both the optimal clock frequency configuration and the resulted minimum energy. We also compare the optimal solution with a brute force flat frequency configuration. Numerical results indicate that our derived optimal solution outperforms the brute-force approach significantly. Moreover, we apply the optimal solution for real-time H.264/AVC video encoding application. Our numerical results suggest that an energy saving of 10%-20% can be achieved, compared to the flat clock frequency scheduling. 2013-09-09T08:07:30Z 2019-12-06T19:56:41Z 2013-09-09T08:07:30Z 2019-12-06T19:56:41Z 2012 2012 Conference Paper https://hdl.handle.net/10356/98544 http://hdl.handle.net/10220/13427 10.1109/ICC.2012.6364132 en © 2012 IEEE. |
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DRNTU::Engineering::Computer science and engineering Yang, Ming Wen, Yonggang Cai, Jianfei Foh, Chuan Heng Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
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This paper investigates the problem of minimizing energy consumption for real-time video encoding on mobile devices, by dynamically configuring the clock frequency in the CPU via the dynamic voltage scaling (DVS) technology. The problem can be formulated as a constrained optimization problem, whose objective is to minimize the total energy consumption of encoding video contents while respecting a real-time delay constraint. Under a probabilistic workload model, we obtain closed-form solutions for both the optimal clock frequency configuration and the resulted minimum energy. We also compare the optimal solution with a brute force flat frequency configuration. Numerical results indicate that our derived optimal solution outperforms the brute-force approach significantly. Moreover, we apply the optimal solution for real-time H.264/AVC video encoding application. Our numerical results suggest that an energy saving of 10%-20% can be achieved, compared to the flat clock frequency scheduling. |
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School of Computer Engineering |
author_facet |
School of Computer Engineering Yang, Ming Wen, Yonggang Cai, Jianfei Foh, Chuan Heng |
format |
Conference or Workshop Item |
author |
Yang, Ming Wen, Yonggang Cai, Jianfei Foh, Chuan Heng |
author_sort |
Yang, Ming |
title |
Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
title_short |
Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
title_full |
Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
title_fullStr |
Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
title_full_unstemmed |
Energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
title_sort |
energy minimization via dynamic voltage scaling for real-time video encoding on mobile devices |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/98544 http://hdl.handle.net/10220/13427 |
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1681056377621970944 |