Online Power-Aware Scheduling Strategy Based on Workload Power Profile Measurement

被引：0

作者：

Popovic, Ivan ^{[1
]}

Jankovic, Strahinja ^{[1
]}

Saranovac, Lazar ^{[1
]}

机构：

[1] Univ Belgrade, Sch Elect Engn, Belgrade, Serbia

来源：

2017 ZOOMING INNOVATION IN CONSUMER ELECTRONICS INTERNATIONAL CONFERENCE (ZINC) | 2017年

关键词：

Power Management; Power profiling; Power-aware; Microcontroller; Real-time Operating System;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Deeply embedded systems represent large portion of devices connected in Internet of Things. Because of great number of deployed devices, power management of deeply embedded systems is an emerging aspect of their operation. The most actual power management techniques are hardware-centric and do not take run-time workload execution properties into account. We propose a novel power aware scheduling strategy for deeply embedded systems. Task-based power profiling is used to generate task power model utilized for power-aware or energy-aware task scheduling. The proposed concept dynamically changes the scheduling parameters of best-effort tasks to fit optimization goal while maintaining system hard real-time requirements. Concept is application design agnostic and can be easily integrated as a power management service available under real-time operating system support.

引用

页码：45 / 46

页数：2

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