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Multiple Pipe Systems

Multiple Pipe Systems

Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...

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Updated: May 10, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

以同行驱动的任务安排和资源配置,以提高工业物联网系统的性能.

Ayman Alfahid¹, Chahira Lhioui², Somia Asklany³

¹Department of Information Systems, College of Computer and Information Sciences, Majmaah University, 11952, Majmaah, Saudi Arabia.

Scientific reports

|April 25, 2025

概括

本研究介绍了一个新的对等依赖的计划和分配方案 (PSAS) 工业物联网 (IIoT) 系统. PSAS使用预测性学习来减少任务延迟,并改善点对点网络中的资源管理.

关键词:

分配计划的分配计划.工业物联网的工业物联网.取决于同行安排的日程安排同行到同行 - 同行到同行.资源分配资源的分配.智能产业是一个智能产业.任务安排任务安排

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相关实验视频

Last Updated: May 10, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Data Communication Based on MQTT in a Polymer Extrusion Process

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Published on: July 15, 2022

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科学领域:

计算机科学计算机科学
工业工程工业工程工业工程
人工智能的人工智能

背景情况:

智能工业中的点对点 (P2P) 系统,加上工业物联网 (IIoT),对于分布式任务管理至关重要.
传统的P2P系统中的顺序资源依赖性可能会导致任务停滞,阻碍效率.
现有的资源分配方法经常与动态任务要求和顺序处理作斗争.

研究的目的:

提出一个新的相互依赖的调度和分配计划 (PSAS),以克服基于P2P的IIoT系统中的任务停滞.
优化任务调度和资源分配,使用预测学习来提高系统吞吐量.
提高智能工业环境中分布式任务处理的可扩展性,可靠性和效率.

主要方法:

开发了一个相互依赖的调度和分配计划 (PSAS),整合了预测学习.
PSAS评估资源的可用性,任务的持续时间,以及为优化决策的最后期限.
基于历史资源利用分析实施实时建议.

主要成果:

PSAS显著减少了任务停滞,并改善了任务处理比率.
与现有方法相比,证明加工率提高了高达10.62%.
实现了5.06%的停滞因子减少,提高了整体系统性能.

结论:

在基于P2P的IIoT系统中,PSAS提供了一个可扩展和可靠的资源管理解决方案.
预测性学习增强了决策,减少了任务完成的延迟.
拟议的方案在优化智能工业的分布式任务处理方面取得了重大进展.