Lightweight Virtualized Industrial Edge Runtime for Software-Defined Automation in Flexible Manufacturing Systems

IF 4.6 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2026-01-01 Epub Date: 2026-09-08 DOI:10.1109/OJIES.2026.3732215

Xinkai Zhang;Shang Gao;Bintao Yu;Wenbin Dai

引用次数: 0

Abstract

Industrial Internet and edge computing provide massive computing resources to legacy industrial automation systems. It also poses critical challenges in handling massive customization requirements. Due to high reconfiguration delays, existing automation systems cannot adapt to those changes in real-time. This article proposes a virtualized industrial edge runtime for software-defined automation systems with a lightweight architecture, rapid startup, fast application launch, and dynamic resource allocation. The proposed runtime system enables dynamic resource reconfiguration with a low memory footprint to address high deployment latency. The experimental results demonstrate that the proposed method can significantly reduce response time and memory usage, thereby meeting real-time constraints for software-defined automation systems.

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柔性制造系统中用于软件定义自动化的轻量级虚拟化工业边缘运行时

工业互联网和边缘计算为传统工业自动化系统提供了大量的计算资源。它在处理大量定制需求方面也提出了严峻的挑战。由于重构的高延迟，现有的自动化系统无法实时适应这些变化。本文为具有轻量级架构、快速启动、快速应用程序启动和动态资源分配的软件定义自动化系统提出了一个虚拟化的工业边缘运行时。建议的运行时系统支持低内存占用的动态资源重新配置，以解决高部署延迟。实验结果表明，该方法可以显著减少响应时间和内存占用，从而满足软件定义自动化系统的实时性要求。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Open Journal of the Industrial Electronics Society ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

10.80

自引率

2.40%

发文量

审稿时长

12 weeks

期刊介绍： The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments. Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.