Abstract
Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) are popular techniques for reducing energy consumption. Algorithms for optimal DVFS exist, but optimal DPM and the optimal combination of DVFS and DPM are not yet solved.
In this article we use well-established models of DPM and DVFS for frame-based systems. We show that it is not sufficient—as some authors argue—to consider only individual invocations of a task. We define a schedule that also takes interactions between invocations into account and prove—in a theoretical fashion—that this schedule is optimal.
- ACPI. 2011. Advanced configuration and power interface standard. http://www.acpi.infoGoogle Scholar
- Augustine, J., Irani, S., and Swamy, C. 2004. Optimal power-down strategies. In Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science. 530--539. Google ScholarDigital Library
- Baptiste, P., Chrobak, M., and Dürr, C. 2007. Polynomial time algorithms for minimum energy scheduling. In Proceedings of the 15th Annual European Conference on Algorithms (ESA'07). Springer, 136--150. Google ScholarDigital Library
- Benini, L., Bogliolo, A., and De Micheli, G. 2000. A survey of design techniques for system-level dynamic power management. IEEE Trans. (VLSI) Syst. 8, 3, 299--316. Google ScholarDigital Library
- Corbae, D., Stinchcombe, M. B., and Zeman, J. 2009. An Introduction to Mathematical Analysis for Economic Theory and Econometrics. Princeton University Press.Google Scholar
- Devadas, V. and Aydin, H. 2008. Real-Time dynamic power management through device forbidden regions. In Proceedings of the Real-Time and Embedded Technology and Applications Symposium, (RTAS'08). IEEE. 34--44. Google ScholarDigital Library
- Devadas, V. and Aydin, H. 2012. On the interplay of voltage/frequency scaling and device power management for frame-based real-time embedded applications. IEEE Trans. Comput. 61, 1, 31--44. Google ScholarDigital Library
- Dijkstra, E. W. 1959. A note on two problems in connexion with graphs. Nume. Math. 1, 1, 269--271.Google ScholarDigital Library
- Hu, F. and Evans, J. 2009. Power and environment aware control of beowulf clusters. Cluster Comput. 12, 3, 299--308. Google ScholarDigital Library
- Huang, W. and Wang, Y. 2009. An optimal speed control scheme supported by media servers for low-power multimedia applications. Multimedia Syst. 15, 2, 113--124.Google ScholarCross Ref
- Ishihara, T. and Yasuura, H. 1998. Voltage scheduling problem for dynamically variable voltage processors. In Proceedings of the 1998 International Symposium on Low Power Electronics and Design (ISLPED'98). ACM, New York, 197--202. Google ScholarDigital Library
- Jejurikar, R. and Gupta, R. 2004. Dynamic voltage scaling for systemwide energy minimization in real-time embedded systems. In Proceedings of the International Symposium on Low Power Electronics and Design (ISLPED'04). ACM, New York, 78--81. Google ScholarDigital Library
- Kong, F., Wang, Y., Deng, Q., and Yi, W. 2010. Minimizing multi-resource energy for real-time systems with discrete operation modes. In Proceedings of the 22nd Euromicro Conference on Real-Time Systems (ECRTS). 113--122. Google ScholarDigital Library
- Kwon, W.-C. and Kim, T. 2005. Optimal voltage allocation techniques for dynamically variable voltage processors. ACM Trans. Embed. Comput. Syst. 4, 1, 211--230. Google ScholarDigital Library
- Lee, W.-K., Lee, S.-W., and Siew, W.-O. 2009. Hybrid model for dynamic power management. IEEE Transactions on Consum. Electron. 55, 2, 656--664. Google ScholarDigital Library
- Lu, Y.-H., Benini, L., and De Micheli, G. 2000. Operating-system directed power reduction. In Proceedings of the 2000 International Symposium on Low Power Electronics and Design (ISLPED'00). ACM, New York, 37--42. Google ScholarDigital Library
- Lu, Y.-H., Benini, L., and De Micheli, G. 2002. Power-aware operating systems for interactive systems. IEEE Trans. (VLSI), Syst. 10, 2, 119--134. Google ScholarDigital Library
- Poess, M. and Nambiar, R. O. 2008. Energy cost, the key challenge of today's data centers: A power consumption analysis of TPC-C results. Proc. VLDB Endow. 1, 2, 1229--1240. Google ScholarDigital Library
- Rusu, C., Melhem, R., and Mossé, D. 2003. Maximizing rewards for real-time applications with energy constraints. ACM Trans. Embed. Comput. Syst. 2, 4, 537--559. Google ScholarDigital Library
- Sinha, A. and Chandrakasan, A. 2001. Dynamic power management in wireless sensor networks. IEEE Design Test Comput. 18, 2, 62--74. Google ScholarDigital Library
- Sueur, L. and Heiser, G. 2010. Dynamic voltage and frequency scaling: The laws of diminishing returns. In Proceedings of the International Conference on Power Aware Computing and Systems (HotPower'10). USENIX Association, 1--8. Google ScholarDigital Library
- Wang, Y., Xie, Q., Ammari, A., and Pedram, M. 2011. Deriving a near-optimal power management policy using model-free reinforcement learning and bayesian classification. In Proceedings of the 48th Design Automation Conference (DAC'11). ACM, New York, 41--46. Google ScholarDigital Library
- Weiser, M., Welch, B., Demers, A., and Shenker, S. 1996. Scheduling for reduced CPU energy. In Mobile Computing, T. Imielinski and H. F. Korth, Eds. The Kluwer International Series in Engineering and Computer Science, Vol. 353. 449--471.Google Scholar
- Xu, R., Melhem, R., and Mossé, D. 2007. A unified practical approach to stochastic DVS scheduling. In Proceedings of the 7th ACM & IEEE International Conference on Embedded Software (EMSOFT'07). ACM, New York, 37--46. Google ScholarDigital Library
- Xu, R., Mossé, D., and Melhem, R. 2005. Minimizing expected energy in real-time embedded systems. In Proceedings of the 5th ACM International Conference on Embedded Software (EMSOFT'05). ACM, New York, 251--254. Google ScholarDigital Library
- Yao, F., Demers, A., and Shenker, S. 1995. A scheduling model for reduced CPU energy. In Proceedings of the IEEE 36th Annual Conference on Foundations of Computer Science. 374--382. Google ScholarDigital Library
- Zhu, Q., David, F. M., Devaraj, C. F., Li, Z., Zhou, Y., and Cao, P. 2004. Reducing energy consumption of disk storage using power-aware cache management. In Proceedings of the 10th International Symposium on High Performance Computer Architecture (HPCA-10). 118--129. Google ScholarDigital Library
- Zitterell, T. and Scholl, C. 2010. A probabilistic and energy-efficient scheduling approach for online application in real-time systems. In Proceedings of the 47th Design Automation Conference (DAC'10). ACM, New York, 42--47. Google ScholarDigital Library
Index Terms
- Optimal DPM and DVFS for frame-based real-time systems
Recommendations
Energy-Aware Scheduling for Real-Time Systems: A Survey
This article presents a survey of energy-aware scheduling algorithms proposed for real-time systems. The analysis presents the main results starting from the middle 1990s until today, showing how the proposed solutions evolved to address the evolution ...
An experimental evaluation of real-time DVFS scheduling algorithms
SYSTOR '12: Proceedings of the 5th Annual International Systems and Storage ConferenceWe implement and experimentally evaluate the timeliness and energy consumption behaviors of fourteen Real-Time Dynamic Voltage and Frequency Scaling (RT-DVFS) schedulers on two hardware platforms. The schedulers include CC-EDF, LA-EDF, REUA, DRA, and ...
Online Energy-Efficient Hard Real-Time Scheduling for Component Oriented Systems
ISORC '12: Proceedings of the 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed ComputingThe energy efficiency becomes one of the most important concerns in mobile electronic systems design with mandatory requirements for low energy consumption, long battery life and low heat dissipation. Dynamic Power Management (DPM) and Dynamic Voltage ...
Comments