Real-energy: A new framework and a case study to evaluate power-aware real-time scheduling algorithms

In the past decades, many algorithms with the goal of achieving energy efficiency have been proposed for scheduling real-time tasks. Due to a lack of a unified testing framework, most of them were evaluated via simulations under their own experimental scenarios. However, finding their performance in real processors is essential if these algorithms are to be used in practice. In this paper, we design a unified framework to evaluate power-aware scheduling algorithms based on a real Intel PXA255 XScale processor, and present a case study to compare several key algorithms using DVS/Shut-Down. The energy efficiency and the quantitative difference in their performance as well as the practical issues found in the implementation of these algorithms are discussed. Our experiments show a gap between the theoretical results and the real results. Our framework not only gives researchers a tool to evaluate their system designs, but also helps them to bridge this gap in their future works.

[1]  David C. Snowdon,et al.  Power Management and Dynamic Voltage Scaling: Myths and Facts , 2005 .

[2]  Rami G. Melhem,et al.  Dynamic and aggressive scheduling techniques for power-aware real-time systems , 2001, Proceedings 22nd IEEE Real-Time Systems Symposium (RTSS 2001) (Cat. No.01PR1420).

[3]  Ragunathan Rajkumar,et al.  Critical power slope: understanding the runtime effects of frequency scaling , 2002, ICS '02.

[4]  F. Frances Yao,et al.  A scheduling model for reduced CPU energy , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[5]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.

[6]  Yann-Hang Lee,et al.  Scheduling techniques for reducing leakage power in hard real-time systems , 2003, 15th Euromicro Conference on Real-Time Systems, 2003. Proceedings..

[7]  Sang Lyul Min,et al.  Performance comparison of dynamic voltage scaling algorithms for hard real-time systems , 2002, Proceedings. Eighth IEEE Real-Time and Embedded Technology and Applications Symposium.

[8]  Kiyoung Choi,et al.  Power optimization of real-time embedded systems on variable speed processors , 2000, IEEE/ACM International Conference on Computer Aided Design. ICCAD - 2000. IEEE/ACM Digest of Technical Papers (Cat. No.00CH37140).

[9]  Joseph Y.-T. Leung,et al.  Handbook of Real-Time and Embedded Systems , 2007 .

[10]  Rajesh K. Gupta,et al.  Procrastination scheduling in fixed priority real-time systems , 2004, LCTES '04.

[11]  Rajesh K. Gupta,et al.  Dynamic slack reclamation with procrastination scheduling in real-time embedded systems , 2005, Proceedings. 42nd Design Automation Conference, 2005..

[12]  Rajesh K. Gupta,et al.  Leakage aware dynamic voltage scaling for real-time embedded systems , 2004, Proceedings. 41st Design Automation Conference, 2004..

[13]  Frank Bellosa,et al.  Process cruise control: event-driven clock scaling for dynamic power management , 2002, CASES '02.