An Energy-Efficient Task Scheduling for Near Real-Time Systems on Heterogeneous Multicore Processors
Summary :
Near real-time periodic tasks, which are popular in multimedia streaming applications, have deadline periods that are longer than the input intervals thanks to buffering. For such applications, the conventional frame-based schedulings cannot realize the optimal scheduling due to their shortsighted deadline assumptions. To realize globally energy-efficient executions of these applications, we propose a novel task scheduling algorithm, which takes advantage of the long deadline period. We confirm our approach can take advantage of the longer deadline period and reduce the average power consumption by up to 18%.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.2 pp.329-338
- Publication Date
- 2020/02/01
- Publicized
- 2019/11/01
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDP7101
- Type of Manuscript
- PAPER
- Category
- Software System
Authors
Takashi NAKADA
Nara Institutet of Science and Technology
Hiroyuki YANAGIHASHI
University of Tokyo
Kunimaro IMAI
Proassist Ltd
Hiroshi UEKI
Renesas Electronics Corporation
Takashi TSUCHIYA
Renesas Electronics Corporation
Masanori HAYASHIKOSHI
Renesas Electronics Corporation
Hiroshi NAKAMURA
University of Tokyo
Keyword
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Takashi NAKADA, Hiroyuki YANAGIHASHI, Kunimaro IMAI, Hiroshi UEKI, Takashi TSUCHIYA, Masanori HAYASHIKOSHI, Hiroshi NAKAMURA, "An Energy-Efficient Task Scheduling for Near Real-Time Systems on Heterogeneous Multicore Processors" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 2, pp. 329-338, February 2020, doi: 10.1587/transinf.2019EDP7101.
Abstract: Near real-time periodic tasks, which are popular in multimedia streaming applications, have deadline periods that are longer than the input intervals thanks to buffering. For such applications, the conventional frame-based schedulings cannot realize the optimal scheduling due to their shortsighted deadline assumptions. To realize globally energy-efficient executions of these applications, we propose a novel task scheduling algorithm, which takes advantage of the long deadline period. We confirm our approach can take advantage of the longer deadline period and reduce the average power consumption by up to 18%.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDP7101/_p
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@ARTICLE{e103-d_2_329,
author={Takashi NAKADA, Hiroyuki YANAGIHASHI, Kunimaro IMAI, Hiroshi UEKI, Takashi TSUCHIYA, Masanori HAYASHIKOSHI, Hiroshi NAKAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={An Energy-Efficient Task Scheduling for Near Real-Time Systems on Heterogeneous Multicore Processors},
year={2020},
volume={E103-D},
number={2},
pages={329-338},
abstract={Near real-time periodic tasks, which are popular in multimedia streaming applications, have deadline periods that are longer than the input intervals thanks to buffering. For such applications, the conventional frame-based schedulings cannot realize the optimal scheduling due to their shortsighted deadline assumptions. To realize globally energy-efficient executions of these applications, we propose a novel task scheduling algorithm, which takes advantage of the long deadline period. We confirm our approach can take advantage of the longer deadline period and reduce the average power consumption by up to 18%.},
keywords={},
doi={10.1587/transinf.2019EDP7101},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - An Energy-Efficient Task Scheduling for Near Real-Time Systems on Heterogeneous Multicore Processors
T2 - IEICE TRANSACTIONS on Information
SP - 329
EP - 338
AU - Takashi NAKADA
AU - Hiroyuki YANAGIHASHI
AU - Kunimaro IMAI
AU - Hiroshi UEKI
AU - Takashi TSUCHIYA
AU - Masanori HAYASHIKOSHI
AU - Hiroshi NAKAMURA
PY - 2020
DO - 10.1587/transinf.2019EDP7101
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2020
AB - Near real-time periodic tasks, which are popular in multimedia streaming applications, have deadline periods that are longer than the input intervals thanks to buffering. For such applications, the conventional frame-based schedulings cannot realize the optimal scheduling due to their shortsighted deadline assumptions. To realize globally energy-efficient executions of these applications, we propose a novel task scheduling algorithm, which takes advantage of the long deadline period. We confirm our approach can take advantage of the longer deadline period and reduce the average power consumption by up to 18%.
ER -
English
