Result: Methods for power optimization in distributed embedded systems with real-time requirements

Title:
Methods for power optimization in distributed embedded systems with real-time requirements
Source:
CASES 2006 (International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, October 22-25, 2006, Seoul, Korea, embedded systems week 2006). :379-388
Publisher Information:
New York NY: ACM Press, 2006.
Publication Year:
2006
Physical Description:
print, 32 ref 1
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
IDA Technical University of Braunschweig, 38106 Braunschweig, Germany
Department of CSE University of Notre Dame, Notre Dame, IN 46556, United States
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19105513
Database:
PASCAL Archive

Further Information

Dynamic voltage scaling and sleep state control have been shown to be extremely effective in reducing energy consumption in CMOS circuits. Though plenty of research papers have studied the application of these techniques in real-time embedded system design through intelligent task and/or voltage scheduling, most of these results are limited to relatively simple real-time application models. In this paper, a comprehensive real-time application model including periodic, sporadic and bursty tasks as well as distributed real-time constraints such as end-to-end delays is considered. Two methods are presented for reducing energy consumption while satisfying complex real-time constraints for this model. Experimental results show that the methods achieve significant energy savings without violating any deadlines.