在5G工业物联网中,基于皮尔森相关性的聚类与协作任务分配在5G工业物联网中分离的健康网络
Krishnakumar Vaithianathan1, Julian Benadit Pernabas2, Manjunath Ramanna Lamani3
1Department of Computer Engineering, Karaikal Polytechnic College, Varichikudy, Karaikal, 609609, Puducherry, India.
Scientific reports
|December 8, 2025
概括
本研究介绍了连接调适应任务分配 (CHATA) 模型,用于工业物联网 (IIoT) 医疗网络中的公平任务分配. 通过考虑任务功能相关性,CHATA提高了任务分配效率,实现高达90%的分配效率.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 事物的工业互联网 (IIoT)
背景情况:
- 任务分配对于工业物联网 (IIoT) 环境中的服务质量至关重要.
- 当前的方法与动态对象管理和任务功能相关性作斗争.
- 需要有效的策略来实现透明的配置和最大化任务吞吐量.
研究的目的:
- 介绍一个新的连接波自适应任务分配 (CHATA) 模型.
- 在IIoT健康网络中确保公平的任务分配.
- 通过利用对象功能的相似性来改进任务分配.
主要方法:
- 开发了连接波自适应任务分配 (CHATA) 模型.
- 使用对象功能的相似性测量用于任务匹配.
- 在5G无线电接入技术IIoT健康环境中使用NS-3进行模拟.
主要成果:
- 在模拟的IIoT健康环境中,CHATA实现了高达90%的分配效率.
- 与最近的方法相比,该模型展示了优越的任务分配性能.
- 有效地解决了将任务与对象功能相关联的挑战.
结论:
- 查塔模型为IIoT的同时任务分配提供了一个有效的解决方案.
- 利用功能相似性可以提高任务分配的公平性和效率.
- CHATA显著提高了支持5G的IIoT医疗网络的性能.
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