在工业物联网中的中断感知计算卸载.
1Department of Electronic Engineering, Soongsil University, Seoul 06978, Republic of Korea.
Sensors (Basel, Switzerland)
|May 14, 2025
概括
本研究介绍了工业物联网 (IIoT) 的中断意识任务卸载框架. 它通过主动管理边缘服务器可用性和任务中断来减少服务延迟.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 网络工程 网络工程
背景情况:
- 工业物联网 (IIoT) 设备的计算能力有限,需要将任务卸载到边缘服务器以提高效率.
- 边缘服务器过载可能会导致中断,影响本地设备的服务可用性.
- 目前的中断缓解策略往往是反应性的,缺乏积极的适应.
研究的目的:
- 为IIoT开发一个主动的任务卸载框架,以考虑潜在的边缘服务器中断.
- 为估计边缘服务器可用性引入一个现实的基于负载的中断模型.
- 为了提高计算效率并减少IIoT网络中的服务延迟.
主要方法:
- 开发了一个基于负载的中断模型,使用计算负载的指数函数来估计服务器可用性.
- 员工多代理优势行为者-关键 (MAA2C) 对于分散的,自适应的卸载决策.
- 整合边缘可用性,资源限制,设备合作和中断概率进入决策.
主要成果:
- 拟议的框架有效地减少了IIoT网络的平均总服务延迟.
- 优化了系统延迟和边缘服务器可用性之间的权衡.
- 证明了框架能够处理中断和资源限制的能力.
结论:
- 具有中断意识的主动任务卸载框架显著提高了IIoT系统的效率.
- MAA2C 方法为复杂的 IIoT 环境提供了有效的分散决策.
- 该研究提供了关于对可中断边缘任务卸载的参数影响的有价值的见解.
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