Static task-scheduling algorithms for battery-powered DVS systems

Princey Chowdhury; Chaitali Chakrabarti

doi:10.1109/TVLSI.2004.840771

Static task-scheduling algorithms for battery-powered DVS systems

Princey Chowdhury, Chaitali Chakrabarti

Research output: Contribution to journal › Article › peer-review

77 Scopus citations

Abstract

Battery lifetime enhancement is a critical design parameter for mobile computing devices. Maximizing the battery lifetime is a particularly difficult problem due to the nonlinearity of the battery behavior and its dependence on the characteristics of the discharge profile. In this paper, we address the problem of task scheduling with voltage scaling in a battery-powered single and multiprocessor system such that the residual charge or the battery voltage (the parameters for evaluating battery performance) is maximized. We propose an efficient heuristic algorithm using a charge-based cost function derived from the analytical battery model. Our algorithm first creates a task sequence that ensures battery survival, and then distributes the available delay slack so that the cost function is maximized. The effectiveness of the algorithm has been verified using DUALFOIL, a low-level Li-ion battery simulator. The algorithm has been validated on synthetic examples created from applications running on Compaq's handheld computing research platform, ITSY.

Original language	English (US)
Pages (from-to)	226-237
Number of pages	12
Journal	IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume	13
Issue number	2
DOIs	https://doi.org/10.1109/TVLSI.2004.840771
State	Published - Feb 2005

Keywords

Battery optimizations
DVS processors
Low power
Scheduling
Voltage scaling

ASJC Scopus subject areas

Software
Hardware and Architecture
Electrical and Electronic Engineering

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10.1109/TVLSI.2004.840771

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abstract = "Battery lifetime enhancement is a critical design parameter for mobile computing devices. Maximizing the battery lifetime is a particularly difficult problem due to the nonlinearity of the battery behavior and its dependence on the characteristics of the discharge profile. In this paper, we address the problem of task scheduling with voltage scaling in a battery-powered single and multiprocessor system such that the residual charge or the battery voltage (the parameters for evaluating battery performance) is maximized. We propose an efficient heuristic algorithm using a charge-based cost function derived from the analytical battery model. Our algorithm first creates a task sequence that ensures battery survival, and then distributes the available delay slack so that the cost function is maximized. The effectiveness of the algorithm has been verified using DUALFOIL, a low-level Li-ion battery simulator. The algorithm has been validated on synthetic examples created from applications running on Compaq's handheld computing research platform, ITSY.",

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note = "Funding Information: Manuscript received April 4, 2003; revised August 24, 2004. This work was supported in part by the NSF/SIUCRC Center for Low Power Electronics and by the NSF/IUCRC Connection One. P. Chowdhury is with Maxim Integrated Products, Sunnyvale, CA 94086 USA (e-mail: princeyc@design.mxim.com). C. Chakrabarti is with the Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-5706 USA (e-mail: chaitali@asu.edu). Digital Object Identifier 10.1109/TVLSI.2004.840771",

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AB - Battery lifetime enhancement is a critical design parameter for mobile computing devices. Maximizing the battery lifetime is a particularly difficult problem due to the nonlinearity of the battery behavior and its dependence on the characteristics of the discharge profile. In this paper, we address the problem of task scheduling with voltage scaling in a battery-powered single and multiprocessor system such that the residual charge or the battery voltage (the parameters for evaluating battery performance) is maximized. We propose an efficient heuristic algorithm using a charge-based cost function derived from the analytical battery model. Our algorithm first creates a task sequence that ensures battery survival, and then distributes the available delay slack so that the cost function is maximized. The effectiveness of the algorithm has been verified using DUALFOIL, a low-level Li-ion battery simulator. The algorithm has been validated on synthetic examples created from applications running on Compaq's handheld computing research platform, ITSY.

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Static task-scheduling algorithms for battery-powered DVS systems

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