As discussed in the previous chapter, offline analysis can be used to generate a schedule of DVFS state changes to minimize energy consumption, while ensuring sufficient processing cycles are available for all tasks to meet their deadlines, even under worst-case computation requirements. However, invocations of real-time tasks typically use less than their specified worst-case computation requirements, presenting an opportunity for further energy conservation. This chapter outlines three online, dynamic techniques to more aggressively scale back processing frequency and voltage to conserve energy when task computation cycles vary, yet continue to provide timeliness guarantees for worst-case execution time scenarios.
Unable to display preview. Download preview PDF.
- DUDANI, A., MUELLER, F., AND ZHU, Y. Energy-conserving feed-back EDF scheduling for embedded systems with real-time constraints. In ACM SIGPLAN Joint Conference Languages, Compilers, and Tools for Embedded Systems (LCTES’02) and Software and Compilers for Embed-ded Systems (SCOPES’02) (June 2002), pp. 213-222.Google Scholar
- GRUIAN, F. Hard real-time scheduling for low energy using stochastic data and DVS processors. In Proceedings of the International Symposium on Low-Power Electronics and Design ISLPED’01 (Huntington Beach, CA, Aug. 2001).Google Scholar
- KIM, W., SHIN, D., YUN, H. -S., KIM, J., AND MIN, S.L. Perfor-mance comparison of dynamic voltage scaling algorithms for hard real-time systems. In Proceedings of the 8th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’02) (2002).Google Scholar
- KRISHNA, C.M., AND LEE, Y. -H. Voltage-clock-scaling techniques for low power in hard real-time systems. In Proceedings of the IEEE Real-Time Technology and Applications Symposium (Washington, DC, May 2000), pp. 156-165.Google Scholar
- KRISHNA, C.M., AND SHIN, K.G. Real-Time Systems. McGraw-Hill, 1997.Google Scholar
- LEHOCZKY, J., SHA, L., AND DING, Y. The rate monotonic scheduling algorithm: exact characterization and average case behavior. In Proceed-ings of the IEEE Real-Time Systems Symposium (1989), pp. 166-171.Google Scholar
- LEHOCZKY, J., AND THUEL, S. Algorithms for scheduling hard aperi-odic tasks in fixed-priority systems using slack stealing. In Proceedings of the IEEE Real-Time Systems Symposium (1994).Google Scholar
- LEHOCZKY, J.P., SHA, L., AND STROSNIDER, J.K. Enhanced aperiodic responsiveness in hard real-time environments. In Proceedings of the 8th IEEE Real-Time Systems Symposium (Los Alamitos, CA, Dec. 1987), pp. 261-270.Google Scholar
- LU, Z., HEIN, J., HUMPHREY, M., STAN, M., LACH, J., AND SKADRON, K. Control-theoretic dynamic frequency and voltage scaling for multimedia workloads. In CASES ’02: Proceedings of the 2002 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (2002), pp. 156-163.Google Scholar
- PILLAI, P., AND SHIN, K. G. Real-time dynamic voltage scaling for low-power embedded operating systems. In Proceedings of the 18th ACM Symposium on Operating Systems Principles (Banff, Alberta, CA, Oct. 2001), pp. 89-102.Google Scholar
- STANKOVIC, J., ET AL. Deadline Scheduling for Real-Time Systems. Kluwer Academic Publishers, 1998.Google Scholar
- SWAMINATHAN, V., AND CHAKRABARTY, K. Real-time task schedul-ing for energy-aware embedded systems. In Proceedings of the IEEE Real-Time Systems Symp. (Work-in-Progress Session) (Orlando, FL, Nov. 2000).Google Scholar
- VARMA, A., GANESH, B., SEN, M., CHOUDHARY, S. R.,SRINIVASAN, L., AND JACOB, B. A control-theoretic approach to dynamic voltage scaling. In Proceedings of International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES 2003) (Oct. 2003), pp. 255-266.Google Scholar
- ZHU, Y., AND MUELLER, F. Feedback EDF scheduling exploiting dynamic voltage scaling. In 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’04) (2004).Google Scholar