We propose a dynamic voltage scaling algorithm to exploit the temporal locality called TLDVS (Temporal Locality DVS) that can achieve significant energy savings while simultaneously preserving timeliness guarantees made by real-time scheduling. Traditionally hard real-time scheduling algorithms assume that the actual computation requirement of tasks would be varied continuously from time to time, but most real-time tasks have a limited number of operational modes changing with temporal locality. Such temporal locality can be exploited for energy savings by scaling down the operating frequency and the supply voltage accordingly. The proposed algorithm does not assume task periodicity, and requires only previous execution time among a priori information on the task set to schedule. Simulation results show that TLDVS achieves up to 25% energy savings compared with OLDVS, and up to 42% over the non-DVS scheduling.
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Yong-Hee KIM, Myoung-Jo JUNG, Cheol-Hoon LEE, "Energy-Aware Real-Time Task Scheduling Exploiting Temporal Locality" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 5, pp. 1147-1153, May 2010, doi: 10.1587/transinf.E93.D.1147.
Abstract: We propose a dynamic voltage scaling algorithm to exploit the temporal locality called TLDVS (Temporal Locality DVS) that can achieve significant energy savings while simultaneously preserving timeliness guarantees made by real-time scheduling. Traditionally hard real-time scheduling algorithms assume that the actual computation requirement of tasks would be varied continuously from time to time, but most real-time tasks have a limited number of operational modes changing with temporal locality. Such temporal locality can be exploited for energy savings by scaling down the operating frequency and the supply voltage accordingly. The proposed algorithm does not assume task periodicity, and requires only previous execution time among a priori information on the task set to schedule. Simulation results show that TLDVS achieves up to 25% energy savings compared with OLDVS, and up to 42% over the non-DVS scheduling.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1147/_p
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@ARTICLE{e93-d_5_1147,
author={Yong-Hee KIM, Myoung-Jo JUNG, Cheol-Hoon LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Energy-Aware Real-Time Task Scheduling Exploiting Temporal Locality},
year={2010},
volume={E93-D},
number={5},
pages={1147-1153},
abstract={We propose a dynamic voltage scaling algorithm to exploit the temporal locality called TLDVS (Temporal Locality DVS) that can achieve significant energy savings while simultaneously preserving timeliness guarantees made by real-time scheduling. Traditionally hard real-time scheduling algorithms assume that the actual computation requirement of tasks would be varied continuously from time to time, but most real-time tasks have a limited number of operational modes changing with temporal locality. Such temporal locality can be exploited for energy savings by scaling down the operating frequency and the supply voltage accordingly. The proposed algorithm does not assume task periodicity, and requires only previous execution time among a priori information on the task set to schedule. Simulation results show that TLDVS achieves up to 25% energy savings compared with OLDVS, and up to 42% over the non-DVS scheduling.},
keywords={},
doi={10.1587/transinf.E93.D.1147},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - Energy-Aware Real-Time Task Scheduling Exploiting Temporal Locality
T2 - IEICE TRANSACTIONS on Information
SP - 1147
EP - 1153
AU - Yong-Hee KIM
AU - Myoung-Jo JUNG
AU - Cheol-Hoon LEE
PY - 2010
DO - 10.1587/transinf.E93.D.1147
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2010
AB - We propose a dynamic voltage scaling algorithm to exploit the temporal locality called TLDVS (Temporal Locality DVS) that can achieve significant energy savings while simultaneously preserving timeliness guarantees made by real-time scheduling. Traditionally hard real-time scheduling algorithms assume that the actual computation requirement of tasks would be varied continuously from time to time, but most real-time tasks have a limited number of operational modes changing with temporal locality. Such temporal locality can be exploited for energy savings by scaling down the operating frequency and the supply voltage accordingly. The proposed algorithm does not assume task periodicity, and requires only previous execution time among a priori information on the task set to schedule. Simulation results show that TLDVS achieves up to 25% energy savings compared with OLDVS, and up to 42% over the non-DVS scheduling.
ER -