Dynamic Voltage Scaling for Multitasking Real-Time Systems With Uncertain Execution Time

Dynamic voltage and frequency scaling can save energy for real-time systems. Frequencies are generally assumed proportional to voltages. Previous studies consider the probabilistic distributions of tasks' execution time to assist dynamic voltage scaling in task scheduling. These studies use probability information for intratask voltage scheduling but do not sufficiently explore the opportunities for intertask scheduling to save more energy. This paper presents a new approach to combine intra- and intertask voltage scheduling for better energy savings in hard real-time systems with uncertain task execution time. Our approach takes three steps: 1) We calculate statistically the optimal voltage schedules for multiple concurrent tasks, using earliest deadline first scheduling for an ideal processor that can change the frequency continuously; 2) we then adapt the solution to a processor with a limited range of discrete frequencies, using a polynomial-time heuristic algorithm; and 3) finally, we improve our solution, considering the time and energy overheads of frequency switching for schedulability and energy reduction. Our simulation shows that the new approach can save more energy than existing solutions while meeting hard deadlines.

[1]  J. Jensen.  Sur les fonctions convexes et les inégalités entre les valeurs moyennes , 1906 .

[2]  Chung Laung Liu,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[3]  Giorgio Buttazzo,et al.  Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications , 1997 .

[4]  Hiroto Yasuura,et al.  Voltage scheduling problem for dynamically variable voltage processors , 1998, Proceedings. 1998 International Symposium on Low Power Electronics and Design (IEEE Cat. No.98TH8379).

[5]  Thomas D. Burd,et al.  Design issues for Dynamic Voltage Scaling , 2000, ISLPED'00: Proceedings of the 2000 International Symposium on Low Power Electronics and Design (Cat. No.00TH8514).

[6]  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).

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

[8]  Alan Jay Smith,et al.  Improving dynamic voltage scaling algorithms with PACE , 2001, SIGMETRICS '01.

[9]  Flavius Gruian.  Hard real-time scheduling for low-energy using stochastic data and DVS processors , 2001, ISLPED '01.

[10]  Frank Mueller,et al.  Energy-conserving feedback EDF scheduling for embedded systems with real-time constraints , 2002, LCTES/SCOPES '02.

[11]  Klara Nahrstedt,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003, SOSP '03.

[12]  Frank Mueller,et al.  Feedback EDF scheduling exploiting dynamic voltage scaling , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..

[13]  Joachim Wegener,et al.  A Comparison of Static Analysis and Evolutionary Testing for the Verification of Timing Constraints , 2004, Real-Time Systems.

[14]  Carlo Tomasi,et al.  Depth Discontinuities by Pixel-to-Pixel Stereo , 1999, International Journal of Computer Vision.

[15]  Rami G. Melhem,et al.  Energy-efficient policies for request-driven soft real-time systems , 2004, Proceedings. 16th Euromicro Conference on Real-Time Systems, 2004. ECRTS 2004..

[16]  Rami G. Melhem,et al.  Practical PACE for embedded systems , 2004, EMSOFT '04.

[17]  Alberto Broggi,et al.  Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[18]  Yung-Hsiang Lu,et al.  A case study of mobile robot's energy consumption and conservation techniques , 2005, ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005..

[19]  Kevin Skadron,et al.  Optimal procrastinating voltage scheduling for hard real-time systems , 2005, Proceedings. 42nd Design Automation Conference, 2005..

[20]  Rami G. Melhem,et al.  Minimizing expected energy in real-time embedded systems , 2005, EMSOFT.

[21]  Yung-Hsiang Lu,et al.  Energy-Effcient Scheduling for Autonomous Mobile Robots , 2006, 2006 IFIP International Conference on Very Large Scale Integration.

[22]  Klara Nahrstedt,et al.  Energy-efficient CPU scheduling for multimedia applications , 2006, TOCS.

[23]  Yung-Hsiang Lu,et al.  Energy Reduction by Workload Adaptation in a Multi-Process Environment , 2006, Proceedings of the Design Automation & Test in Europe Conference.

[24]  Kevin Skadron,et al.  Procrastinating voltage scheduling with discrete frequency sets , 2006, Proceedings of the Design Automation & Test in Europe Conference.

[25]  Zhiyuan Li,et al.  Energy-Aware Scheduling for Real-Time Multiprocessor Systems with Uncertain Task Execution Time , 2007, 2007 44th ACM/IEEE Design Automation Conference.

[26]  Yung-Hsiang Lu,et al.  Dynamic Voltage Scaling for Multitasking Real-Time Systems With Uncertain Execution Time , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.