An Approximation Algorithm for Energy-Efficient Scheduling on A Chip Multiprocessor

In the recent decade, voltage scaling has become an attractive feature for many system component designs. In this paper, we consider energy-efficient real-time task scheduling over a chip multiprocessor architecture. The objective is to schedule a set of frame-based tasks with the minimum energy con...

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Published in:Design, Automation and Test in Europe pp. 468 - 473
Main Authors: Yang, Chuan-Yue, Chen, Jian-Jia, Kuo, Tei-Wei
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 07.03.2005
IEEE
Series:ACM Conferences
Subjects:
Algorithm design and analysis
Approximation algorithms
Computer systems organization > Architectures > Parallel architectures > Multiple instruction, multiple data
Computing methodologies > Symbolic and algebraic manipulation > Symbolic and algebraic algorithms
Delay
Energy consumption
Energy efficiency
Frequency
Mathematics of computing > Mathematical analysis > Functional analysis > Approximation
Processor scheduling
Scheduling algorithm
Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Process management > Scheduling
Switches
Theory of computation > Computational complexity and cryptography > Problems, reductions and completeness
Theory of computation > Design and analysis of algorithms
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis
Threshold voltage
ISBN:9780769522883, 0769522882
ISSN:1530-1591
Online Access:Get full text
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Summary:In the recent decade, voltage scaling has become an attractive feature for many system component designs. In this paper, we consider energy-efficient real-time task scheduling over a chip multiprocessor architecture. The objective is to schedule a set of frame-based tasks with the minimum energy consumption, where all tasks are ready at time 0 and share a common deadline. We show that such a minimization problem is NP-hard and then propose a 2 .371-approximation algorithm. The strength of the proposed algorithm was demonstrated by a series of simulations, for which near optimal results were obtained.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780769522883
0769522882
ISSN:1530-1591
DOI:10.1109/DATE.2005.51