An Energy-Efficient Task Scheduling for Near-Realtime Systems with Execution Time Variation

Takashi NAKADA; Tomoki HATANAKA; Hiroshi UEKI; Masanori HAYASHIKOSHI; Toru SHIMIZU; Hiroshi NAKAMURA

doi:10.1587/transinf.2016EDP7497

An Energy-Efficient Task Scheduling for Near-Realtime Systems with Execution Time Variation

Takashi NAKADA, Tomoki HATANAKA, Hiroshi UEKI, Masanori HAYASHIKOSHI, Toru SHIMIZU, Hiroshi NAKAMURA

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Improving energy efficiency is critical for embedded systems in our rapidly evolving information society. Near real-time data processing tasks, such as multimedia streaming applications, exhibit a common fact that their deadline periods are longer than their input intervals due to buffering. In general, executing tasks at lower performance is more energy efficient. On the other hand, higher performance is necessary for huge tasks to meet their deadlines. To minimize the energy consumption while meeting deadlines strictly, adaptive task scheduling including dynamic performance mode selection is very important. In this work, we propose an energy efficient slack-based task scheduling algorithm for such tasks by adapting to task size variations and applying DVFS with the help of statistical analysis. We confirmed that our proposal can further reduce the energy consumption when compared to oracle frame-based scheduling.

Publication: IEICE TRANSACTIONS on Information Vol.E100-D No.10 pp.2493-2504

Publication Date: 2017/10/01

Publicized: 2017/06/26

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2016EDP7497

Type of Manuscript: PAPER

Category: Software System

Authors

Takashi NAKADA
  Nara Institutet of Science and Technology
Tomoki HATANAKA
  University of Tokyo
Hiroshi UEKI
  Renesas Electronics Corporation
Masanori HAYASHIKOSHI
  Renesas Electronics Corporation
Toru SHIMIZU
  Keio University
Hiroshi NAKAMURA
  University of Tokyo

Keyword

adaptive task scheduling, near real-time processing, execution time variation, energy efficiency

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Takashi NAKADA, Tomoki HATANAKA, Hiroshi UEKI, Masanori HAYASHIKOSHI, Toru SHIMIZU, Hiroshi NAKAMURA, "An Energy-Efficient Task Scheduling for Near-Realtime Systems with Execution Time Variation" in IEICE TRANSACTIONS on Information, vol. E100-D, no. 10, pp. 2493-2504, October 2017, doi: 10.1587/transinf.2016EDP7497.
Abstract: Improving energy efficiency is critical for embedded systems in our rapidly evolving information society. Near real-time data processing tasks, such as multimedia streaming applications, exhibit a common fact that their deadline periods are longer than their input intervals due to buffering. In general, executing tasks at lower performance is more energy efficient. On the other hand, higher performance is necessary for huge tasks to meet their deadlines. To minimize the energy consumption while meeting deadlines strictly, adaptive task scheduling including dynamic performance mode selection is very important. In this work, we propose an energy efficient slack-based task scheduling algorithm for such tasks by adapting to task size variations and applying DVFS with the help of statistical analysis. We confirmed that our proposal can further reduce the energy consumption when compared to oracle frame-based scheduling.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2016EDP7497/_p

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@ARTICLE{e100-d_10_2493,
author={Takashi NAKADA, Tomoki HATANAKA, Hiroshi UEKI, Masanori HAYASHIKOSHI, Toru SHIMIZU, Hiroshi NAKAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={An Energy-Efficient Task Scheduling for Near-Realtime Systems with Execution Time Variation},
year={2017},
volume={E100-D},
number={10},
pages={2493-2504},
abstract={Improving energy efficiency is critical for embedded systems in our rapidly evolving information society. Near real-time data processing tasks, such as multimedia streaming applications, exhibit a common fact that their deadline periods are longer than their input intervals due to buffering. In general, executing tasks at lower performance is more energy efficient. On the other hand, higher performance is necessary for huge tasks to meet their deadlines. To minimize the energy consumption while meeting deadlines strictly, adaptive task scheduling including dynamic performance mode selection is very important. In this work, we propose an energy efficient slack-based task scheduling algorithm for such tasks by adapting to task size variations and applying DVFS with the help of statistical analysis. We confirmed that our proposal can further reduce the energy consumption when compared to oracle frame-based scheduling.},
keywords={},
doi={10.1587/transinf.2016EDP7497},
ISSN={1745-1361},
month={October},}

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TY - JOUR
TI - An Energy-Efficient Task Scheduling for Near-Realtime Systems with Execution Time Variation
T2 - IEICE TRANSACTIONS on Information
SP - 2493
EP - 2504
AU - Takashi NAKADA
AU - Tomoki HATANAKA
AU - Hiroshi UEKI
AU - Masanori HAYASHIKOSHI
AU - Toru SHIMIZU
AU - Hiroshi NAKAMURA
PY - 2017
DO - 10.1587/transinf.2016EDP7497
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2017
AB - Improving energy efficiency is critical for embedded systems in our rapidly evolving information society. Near real-time data processing tasks, such as multimedia streaming applications, exhibit a common fact that their deadline periods are longer than their input intervals due to buffering. In general, executing tasks at lower performance is more energy efficient. On the other hand, higher performance is necessary for huge tasks to meet their deadlines. To minimize the energy consumption while meeting deadlines strictly, adaptive task scheduling including dynamic performance mode selection is very important. In this work, we propose an energy efficient slack-based task scheduling algorithm for such tasks by adapting to task size variations and applying DVFS with the help of statistical analysis. We confirmed that our proposal can further reduce the energy consumption when compared to oracle frame-based scheduling.
ER -