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  

IEICE TRANSACTIONS on Information and Systems   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
adaptive task scheduling,  near real-time processing,  execution time variation,  energy efficiency,  

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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.