基于调度器的物联网设备能耗优化策略

赵婉芳; 韩勇

doi:10.11959/j.issn.1000-0801.2019043

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基于调度器的物联网设备能耗优化策略

研究与开发 | 更新时间：2024-06-05

- 基于调度器的物联网设备能耗优化策略
- Energy optimization strategy on the IoT equipment based on the scheduler
- 电信科学 2019年35卷第3期页码：84-90
- 作者机构：
  
  1. 北京电子科技职业学院，北京 100176
  2. 北京邮电大学，北京 1000876
  3. 联通信息导航有限公司，北京 100032
- 作者简介：
  
  [ "赵婉芳（1975- ），女，北京电子科技职业学院副教授，主要研究方向为物联网嵌入式开发及网络软件应用与开发等。" ]
  [ "韩勇（1980- ），男，北京邮电大学博士生，联通信息导航有限公司高级工程师，主要研究方向为物联网开发、大数据的应用及开发。" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2019043
  中图分类号： TP311.13
- 网络出版日期：2019-03，
  
  纸质出版日期：2019-03-20
- 稿件说明：
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赵婉芳, 韩勇. 基于调度器的物联网设备能耗优化策略[J]. 电信科学, 2019,35(3):84-90.

Wanfang ZHAO, Yong HAN. Energy optimization strategy on the IoT equipment based on the scheduler[J]. Telecommunications science, 2019, 35(3): 84-90.
赵婉芳, 韩勇. 基于调度器的物联网设备能耗优化策略[J]. 电信科学, 2019,35(3):84-90. DOI： 10.11959/j.issn.1000-0801.2019043.

Wanfang ZHAO, Yong HAN. Energy optimization strategy on the IoT equipment based on the scheduler[J]. Telecommunications science, 2019, 35(3): 84-90. DOI： 10.11959/j.issn.1000-0801.2019043.

摘要

针对物联网边缘节点能源消耗需求快速增长问题，提出一种调度器优化策略，整体降低边缘节点能耗。在典型的物联网多核终端系统的电源管理架构及能耗特性的基础上，分析现有 Linux 系统电源管理存在的不足，提出改进调度器策略来优化系统能耗控制，并给出了该策略的实现过程及实施要点。该策略在多核模拟系统中进行了测试，结果表明，在低负载的运行场景，即CPU不需要进行大规模运算处理的情境下，如数据采集、设备监控等物联网典型应用场景，该策略节能效果明显。

Abstract

A scheduling strategy to optimize energy consumption was proposed to reduce the energy consumption of the edge system in view of the fast growth of energy consumption demand in the internet of things.Based on the analysis of the power management architecture and the energy consumption composition in the typical multi-core terminal system

in view of the shortcomings of the existing system power management module

the scheduler load balancing mechanism was improved to control system energy consumption and the implementation process and implementation points of the strategy were given.The strategy was tested in the multi-core simulation system.The result shows that in low load scenarios

that is

in scenarios that CPU does not need to do data-intensive computing

the energy-saving effect of this strategy is obvious

such as data acquisition

equipment monitoring and other typical internet of things applications.

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references

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