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Energy efficient DVS schedule for fixed-priority real-time systems

Published:01 September 2007Publication History
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Abstract

Energy consumption has become an increasingly important consideration in designing many real-time embedded systems. Variable voltage processors, if used properly, can dramatically reduce such system energy consumption. In this paper, we present a technique to determine voltage settings for a variable voltage processor that utilizes a fixed-priority assignment to schedule jobs. By exploiting more efficiently the processor slack time, our approach can be more effective in reducing the execution speed for real-time tasks when necessary. Our approach also produces the minimum constant voltage needed to feasibly schedule the entire job set. With both randomly generated and practical examples, our heuristic approach can achieve the dynamic energy reduction very close to the theoretically optimal one (within 2%) with much less computation cost.

References

  1. Aydin, H., Melhem, R., Mosse, D., and Alvarez, P. 2001a. Determining optimal processor speeds for periodic real-time tasks with different power characteristics. ECRTS, 225--232. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Aydin, H., Melhem, R., Mosse, D., and Alvarez, P. 2001b. Dynamic and aggressive scheduling techniques for power aware real-time systems. RTSS, 95--105. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Burd, T. 2001. Energy-Efficient Processor System Design. Ph.D. Thesis, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley.Google ScholarGoogle Scholar
  4. Burd, T. D. and Brodersen, R. W. 2000. Design issues for dynamic voltage scaling. ISLPED, 9--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Burns, A., Tindell, K., and Wellings, A. 1995. Effective analysis for engineering real-time fixed priority schedulers. IEEE Transactions on Software Engineering 21, 920--934. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Duarte, D., Vijaykrishnan, N., Irvin, M., Kim, H., and McFarland, G. 2002. Impact of scaling on the effectiveness of dynamic power reduction schemes. ICCD. 382--387.Google ScholarGoogle Scholar
  7. Govil, K., Chan, E., and Wasserman, H. 1995. Comparing algorithms for dynamic speed-setting of a low-power cpu. International Conference on Mobile Computing and Networking. 13--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Gutnik, V. and Chandrakasan, A. 1996. An efficient controller for variable supply-voltage low power processing. Symposium on VLSI Circuits. 158--159.Google ScholarGoogle Scholar
  9. Hong, I., Kirovski, D., Qu, G., Potkonjak, M., and Srivastava, M. B. 1998. Power optimization of variable voltage core-based systems. Proceedings of DAC. 176--181. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Hwang, C. and Wu, A. 1997. A predictive system shutdown method for energy saving of event-driven computation. Proceedings of International Conference on Compter Aided Design. 28--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Intel. Strongarm processors. http://developer.intel.com/design/strong/sa1100.htm.Google ScholarGoogle Scholar
  12. Irani, S., Shukla, S., and Gupta, R. 2003. Algorithms for power savings. SODA. 37--46. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ishihara, T. and Yasuura, H. 1998. Voltage scheduling problem for dynamically variable voltage processors. ISLPED. 197--202. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. ITRS. http://public.itrs.net/. International Technology Roadmap for Semiconductors. International SEMATECH, Austin, TX.Google ScholarGoogle Scholar
  15. Jejurikar, R. and Gupta, R. 2002. Energy aware edf scheduling with task synchronization for embedded real time operating systems. COLP. 71--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Jejurikar, R., Pereira, C., and Gupta, R. 2004. Leakage aware dynamic voltage scaling for real-time embedded systems. DAC. 275--280. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Kim, N., Ryu, M., Hong, S., Saksena, M., Choi, C., and Shin, H. 1996. Visual assessment of a real-time system design: a case study on a cnc controller. RTSS. 300--310. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Kim, W., Kim, J., and Min, S. L. 2002. A dynamic voltage scaling algorithm for dynamic-priority hard real-time systems using slack analysis. DATE. 788--794. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Kim, W., Kim, J., and Min, S. L. 2003. Dynamic voltage scaling algorithm for dynamic priority hard real-time systems using work-demand analysis. ISLPED. 396--401. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Kwon, W. and Kim, T. 2005. Optimal voltage allocation techniques for dynamicaly variable voltage processors. ACM Transactions on Embedded Computing Systems 4, 1, 211--230. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Lehoczky, J., Sha, L., and Ding, Y. 1989. The rate monotonic scheduling algorithm: Exact characterization and average case behavior. RTSS. 166--171.Google ScholarGoogle Scholar
  22. Liu, C. L. and Layland, J. W. 1973. Scheduling algorithms for multiprogramming in a hard real-time environment. Journal of the ACM 17, 2, 46--61. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Liu, J. 2000. Real-Time Systems. Prentice Hall, Englewood Cliff, NJ.Google ScholarGoogle Scholar
  24. Lorch, J. R. and Smith, A. J. 2001. Improving dynamic voltage scaling algorithms with PACE. In SIGMETRICS/Performance. 50--61. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Makzak, A. and Chakrabarti, C. 2003. Variable voltage task scheduling algorithms for minimizing energy/power. IEEE Transactions on VLSI 11, 2 (Apr.), 270--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Mochocki, B., Hu, X., and Quan, G. 2007. Transition overhead aware voltage scheduling for fixed-priority real-time system. ACM Trans. Des. Automat. Electron. Syst. (to appear). Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Mochocki, B., Hu, X., and Quan, G. 2002. A realistic variable voltage scheduling model for real-time applications. ICCAD. 726--731. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Mochocki, B., Hu, X., and Quan, G. 2004. A unified approach to variable voltage scheduling for nonideal dvs processors. IEEE Trans. on Computer-Aided Design for Integrated Circuits and Systems 23, 9, 1370--1377. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Mochocki, B., Hu, X., and Quan, G. 2005. Practical on-line dvs scheduling for a fixed-priority real-time system. RTAS. 224--233. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Namgoong, W., Yu, M., and Meng, T. 1997. A high-efficiency variable-voltage cmos dynamic dc-dc switching regulator. IEEE Internation Solid-State Circuits Conference. 380--381.Google ScholarGoogle Scholar
  31. Nielsen, L., Niessen, C., Sparso, J., and Berkel, K. 1994. Low-power operation using self-timing circuits and adaptive scaling of supply voltage. IEEE Transactions on VLSI and Systems 2, 425--435. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Niu, L. and Quan, G. 2004. Reducing both the dynamic and leakage energy consumption for hard real-time systems. CASES. 140--148. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Pering, T., Burd, T., and Brodersen, R. 1998. The simulation and evaluation of dynamic voltage scaling algorithms. ISLPED. 76--81. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Pering, T., Burd, T., and Burd, R. B. 2000. Voltage scheduling in the Iparm microprocessor system. ISLPED. 96--101. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Pillai, P. and Shin, K. G. 2001. Real-time dynamic voltage scaling for low-power embedded operating systems. In SOSP. 89--102. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Pouwelse, J., Langendoen, K., and Sips, H. 2001. Dynamic voltage scaling on a low power microprocessor. SIGMOBILE. 251--259. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Quan, G. and Hu, X. S. 2001. Energy efficient fixed-priority scheduling for real-time systems on voltage variable processors. DAC. 828--833. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Quan, G. and Hu, X. 2003. Minimum energy fixed-priority scheduling for variable voltage processors. IEEE Transactions on ICCAD 22, 8 (Aug.), 1062--1971.Google ScholarGoogle Scholar
  39. Quan, G., Niu, L., Hu, X., and Mochocki, B. 2004. Fixed priority scheduling for reducing overall energy on variable voltage processors. RTSS. 309--318. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Quan, G., Niu, L., Mochocki, B., and Hu, X. 2007. Fixed-priority scheduling for reducing both the dynamic and leackage energy on variable voltage processors. International Journal of Embedded Systems on Low Power Embedded Computing. (to appear).Google ScholarGoogle Scholar
  41. Rabaey, J. and Pedram, M. 1996. Low Power Design Methodologies. Kluwer Academic Publ., Novell, MA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Shin, D., Kim, J., and Lee, S. 2001. Intra-task voltage scheduling for low-energy hard real-time applications. IEEE Design and Test of Computers 18, 2 (Mar.--Apr.), 20--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Shin, Y. and Choi, K. 1999. Power conscious fixed priority scheduling for hard real-time systems. DAC. 134--139. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Shin, Y., Choi, K., and Sakurai, T. 2000. Power optimization of real-time embedded systems on variable speed processors. ICCAD. 365--368. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Sinha, A. and Chandrakasan, A. P. 2001. Jouletrack- a web based tool for software energy profiling. DAC. 220--225. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Transmeta-Corporation. January, 2000. TM5400 processor specifications. http://www.transmeta. com/crusoe/download/pdf/TMS5400_ProductBrief_5-23-00.pdf.Google ScholarGoogle Scholar
  47. Weiser, M., Welch, B., Demers, A., and Shenker, S. 1994. Scheduling for reduced cpu energy. Proceedings of USENIX Symposium on Operating System Design and Implementation, 13--23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Yan, L., Luo, J., and Jha, N. 2003. Combined dynamic voltage scaling and adaptive body biasing for heterogeneous distributed real-time embedded systems. ICCAD. 30--37. Google ScholarGoogle ScholarCross RefCross Ref
  49. Yao, F., Demers, A., and Shenker, S. 1995. A scheduling model for reduced cpu energy. IEEE Annual Foundations of Comp. Sci. 374--382. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Yun, H.-S. and Kim, J. 2003. On energy optimal voltage scheduling for fixed-prioirty hard real-time systems. ACM Transactions on Embedded Computing Systems 2, 3, 393--430. Google ScholarGoogle ScholarDigital LibraryDigital Library

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