Proceedings of the 6th international workshop on Hardware/software codesign
The simulation and evaluation of dynamic voltage scaling algorithms
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
LEneS: task scheduling for low-energy systems using variable supply voltage processors
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Hybrid global/local search strategies for dynamic voltage scaling in embedded multiprocessors
Proceedings of the ninth international symposium on Hardware/software codesign
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems
Proceedings of the conference on Design, automation and test in Europe
Variable voltage task scheduling for minimizing energy or minimizing power
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Reliability analysis of on-chip communication architectures: An MPEG-2 video decoder case study
Microprocessors & Microsystems
Hi-index | 0.00 |
In this paper, we present a power-aware scheduling scheme for hard real-time embedded systems design. Our new approach can enhance the efficiency of both dynamic voltage scaling (DVS) and dynamic Vth scaling (DVTS). While optimizing the schedule in the time domain, the priorities of the tasks are modified dynamically based on their contribution to the overall power/energy reduction. The scheduling scheme leads to better “distribution” and “utilization” of slack intervals in the system which in return improves the efficiency of voltage scaling techniques. The voltage schedule is generated based on a global view of the components' energy profile when executing different tasks. The experimental results prove the applicability of our approach.