Power conscious fixed priority scheduling for hard real-time systems
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Engineering and Analysis of Fixed Priority Schedulers
IEEE Transactions on Software Engineering
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Proceedings of the conference on Design, automation and test in Europe
A Dynamic Voltage Scaling Algorithm for Sporadic Tasks
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Leakage aware dynamic voltage scaling for real-time embedded systems
Proceedings of the 41st annual Design Automation Conference
On-Line Dynamic Voltage Scaling for Hard Real-Time Systems Using the EDF Algorithm
RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
Dynamic slack reclamation with procrastination scheduling in real-time embedded systems
Proceedings of the 42nd annual Design Automation Conference
Power-aware scheduling and dynamic voltage setting for tasks running on a hard real-time system
ASP-DAC '06 Proceedings of the 2006 Asia and South Pacific Design Automation Conference
System-Level Energy Management for Periodic Real-Time Tasks
RTSS '06 Proceedings of the 27th IEEE International Real-Time Systems Symposium
IEEE Transactions on Computers
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
On-Line Dynamic Voltage Scaling on Processor with Discrete Frequency and Voltage Levels
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Scheduling Sporadic, Hard Real-Time Tasks with Resources
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
A Generalized Framework for System-Wide Energy Savings in Hard Real-Time Embedded Systems
EUC '08 Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 01
CODES+ISSS '11 Proceedings of the seventh IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
IEEE Transactions on Computers
Energy Management under General Task-Level Reliability Constraints
RTAS '12 Proceedings of the 2012 IEEE 18th Real Time and Embedded Technology and Applications Symposium
Dynamic voltage scaling of mixed task sets in priority-driven systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Energy-aware preemptive scheduling algorithm for sporadic tasks on DVS platform
Microprocessors & Microsystems
Dynamic Voltage Scaling for Power-aware Hierarchical Real-Time Scheduling Framework
CSE '12 Proceedings of the 2012 IEEE 15th International Conference on Computational Science and Engineering
Proceedings of the 50th Annual Design Automation Conference
Energy and transition-aware runtime task scheduling for multicore processors
Journal of Parallel and Distributed Computing
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In this paper, we consider the generalized power model in which the focus is the dynamic power and the static power, and we study the problem of the canonical sporadic task scheduling based on the rate-monotonic (RM) scheme. Moreover, we combine with the dynamic voltage scaling (DVS) and dynamic power management (DPM). We present a static low power sporadic tasks scheduling algorithm (SSTLPSA), assuming that each task presents its worst-case work-load to the processor at every instance. In addition, a more energy efficient approach called a dynamic low power sporadic tasks scheduling algorithm (DSTLPSA) is proposed, based on reclaiming the dynamic slack and adjusting the speed of other tasks on-the-fly in order to reduce energy consumption while still meeting the deadlines. The experimental results show that the SSTLPSA algorithm consumes 26.55-38.67% less energy than that of the RM algorithm and the DSTLPSA algorithm reduces the energy consumption up to 18.38-30.51% over the existing DVS algorithm.