The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
DVS(동적 전압 스케일링) 시스템의 비주기적 및 주기적 작업 세트 모두에 대한 배터리 인식 전압 스케줄링 알고리즘의 우수한 설계 원칙이 제시됩니다. 제안된 알고리즘은 여러 배터리 특성과 라그랑주 승수에 의해 제안된 그리디 휴리스틱을 기반으로 합니다. 제안하는 알고리즘을 구성하기 위해 스케줄링 초기 단계의 배터리 특성을 보다 적절하게 사용한다. 결과적으로, 제안된 알고리즘은 각각 단일 프로세서 플랫폼과 다중 프로세서 플랫폼에서 비교 작업에서 발췌한 작업 세트의 주기적 및 비주기적 작업의 합성 예에 대해 우수한 결과를 보여줍니다. 특히 일부 대규모 작업 세트의 경우 제안된 알고리즘을 사용하면 배터리 소모로 인해 이전에 예약할 수 없었던 작업 세트를 예약할 수 있습니다.
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Tetsuo YOKOYAMA, Gang ZENG, Hiroyuki TOMIYAMA, Hiroaki TAKADA, "Static Task Scheduling Algorithms Based on Greedy Heuristics for Battery-Powered DVS Systems" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 10, pp. 2737-2746, October 2010, doi: 10.1587/transinf.E93.D.2737.
Abstract: The principles for good design of battery-aware voltage scheduling algorithms for both aperiodic and periodic task sets on dynamic voltage scaling (DVS) systems are presented. The proposed algorithms are based on greedy heuristics suggested by several battery characteristics and Lagrange multipliers. To construct the proposed algorithms, we use the battery characteristics in the early stage of scheduling more properly. As a consequence, the proposed algorithms show superior results on synthetic examples of periodic and aperiodic tasks from the task sets which are excerpted from the comparative work, on uni- and multi-processor platforms, respectively. In particular, for some large task sets, the proposed algorithms enable previously unschedulable task sets due to battery exhaustion to be schedulable.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2737/_p
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@ARTICLE{e93-d_10_2737,
author={Tetsuo YOKOYAMA, Gang ZENG, Hiroyuki TOMIYAMA, Hiroaki TAKADA, },
journal={IEICE TRANSACTIONS on Information},
title={Static Task Scheduling Algorithms Based on Greedy Heuristics for Battery-Powered DVS Systems},
year={2010},
volume={E93-D},
number={10},
pages={2737-2746},
abstract={The principles for good design of battery-aware voltage scheduling algorithms for both aperiodic and periodic task sets on dynamic voltage scaling (DVS) systems are presented. The proposed algorithms are based on greedy heuristics suggested by several battery characteristics and Lagrange multipliers. To construct the proposed algorithms, we use the battery characteristics in the early stage of scheduling more properly. As a consequence, the proposed algorithms show superior results on synthetic examples of periodic and aperiodic tasks from the task sets which are excerpted from the comparative work, on uni- and multi-processor platforms, respectively. In particular, for some large task sets, the proposed algorithms enable previously unschedulable task sets due to battery exhaustion to be schedulable.},
keywords={},
doi={10.1587/transinf.E93.D.2737},
ISSN={1745-1361},
month={October},}
부
TY - JOUR
TI - Static Task Scheduling Algorithms Based on Greedy Heuristics for Battery-Powered DVS Systems
T2 - IEICE TRANSACTIONS on Information
SP - 2737
EP - 2746
AU - Tetsuo YOKOYAMA
AU - Gang ZENG
AU - Hiroyuki TOMIYAMA
AU - Hiroaki TAKADA
PY - 2010
DO - 10.1587/transinf.E93.D.2737
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2010
AB - The principles for good design of battery-aware voltage scheduling algorithms for both aperiodic and periodic task sets on dynamic voltage scaling (DVS) systems are presented. The proposed algorithms are based on greedy heuristics suggested by several battery characteristics and Lagrange multipliers. To construct the proposed algorithms, we use the battery characteristics in the early stage of scheduling more properly. As a consequence, the proposed algorithms show superior results on synthetic examples of periodic and aperiodic tasks from the task sets which are excerpted from the comparative work, on uni- and multi-processor platforms, respectively. In particular, for some large task sets, the proposed algorithms enable previously unschedulable task sets due to battery exhaustion to be schedulable.
ER -