Proceedings of the 46th Annual Design Automation Conference
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A probabilistic and energy-efficient scheduling approach for online application in real-time systems
Proceedings of the 47th Design Automation Conference
Optimality and improvement of dynamic voltage scaling algorithms for multimedia applications
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Low-energy GALS NoC with FIFO-Monitoring dynamic voltage scaling
Microelectronics Journal
Optimizing quality of service in real-time systems under energy constraints
ACM SIGOPS Operating Systems Review
Power Analysis Attack Resistance Engineering by Dynamic Voltage and Frequency Scaling
ACM Transactions on Embedded Computing Systems (TECS)
Deadline and energy constrained dynamic resource allocation in a heterogeneous computing environment
The Journal of Supercomputing
Temperature-aware idle time distribution for leakage energy optimization
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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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.