• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

无线工业传感器网络:QoS评估与QoS管理框架

Wireless industrial sensor networks: framework for QoS assessment and QoS management.

作者信息

Howitt Ivan, Manges Wayne W, Kuruganti Phani Teja, Allgood Glenn, Gutierrez José A, Conrad James M

机构信息

ECE Department, University of North Carolina at Charlotte, 28223, USA.

出版信息

ISA Trans. 2006 Jul;45(3):347-59. doi: 10.1016/s0019-0578(07)60217-1.

DOI:10.1016/s0019-0578(07)60217-1
PMID:16856632
Abstract

This paper presents a framework that addresses Quality of Service (QoS) for industrial wireless sensor networks as a real-time measurable set of parameters within the context of feedback control, thereby facilitating QoS management. This framework is based on examining the interaction between the industrial control processes and the wireless network. Control theory is used to evaluate the impact of the control/communication interaction, providing a methodology for defining, measuring, and quantifying QoS requirements. An example is presented illustrating the wireless industrial sensor network (WISN) QoS management framework for providing dynamic QoS control within WISN. The example focuses on WISN operating in a time-varying RF interference environment in order to manage application-driven QoS latency constraints.

摘要

本文提出了一个框架,该框架将工业无线传感器网络的服务质量(QoS)作为反馈控制环境下一组可实时测量的参数来处理,从而便于进行QoS管理。此框架基于研究工业控制过程与无线网络之间的交互。控制理论用于评估控制/通信交互的影响,提供一种定义、测量和量化QoS要求的方法。给出了一个示例,说明了用于在无线工业传感器网络(WISN)内提供动态QoS控制的WISN QoS管理框架。该示例重点关注在时变射频干扰环境中运行的WISN,以管理应用驱动的QoS延迟约束。

相似文献

1
Wireless industrial sensor networks: framework for QoS assessment and QoS management.无线工业传感器网络:QoS评估与QoS管理框架
ISA Trans. 2006 Jul;45(3):347-59. doi: 10.1016/s0019-0578(07)60217-1.
2
D-MSR: a distributed network management scheme for real-time monitoring and process control applications in wireless industrial automation.D-MSR:一种用于无线工业自动化中实时监测和过程控制应用的分布式网络管理方案。
Sensors (Basel). 2013 Jun 27;13(7):8239-84. doi: 10.3390/s130708239.
3
QOS-aware error recovery in wireless body sensor networks using adaptive network coding.基于自适应网络编码的无线体域网中QoS感知的错误恢复
Sensors (Basel). 2014 Dec 29;15(1):440-64. doi: 10.3390/s150100440.
4
On service differentiation in mobile Ad Hoc networks.论移动自组织网络中的服务差异化
J Zhejiang Univ Sci. 2004 Sep;5(9):1087-94. doi: 10.1631/jzus.2004.1087.
5
Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.用于提高工业网络中多媒体实时传输性能的动态服务质量模型
PLoS One. 2014 Aug 29;9(8):e105885. doi: 10.1371/journal.pone.0105885. eCollection 2014.
6
Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.针对无线传感器网络中的服务组合应用,分析具有安全约束的综合服务质量。
Sensors (Basel). 2014 Dec 1;14(12):22706-36. doi: 10.3390/s141222706.
7
Designing area optimized application-specific network-on-chip architectures while providing hard QoS guarantees.设计面积优化的专用片上网络架构,同时提供严格的QoS保证。
PLoS One. 2015 Apr 21;10(4):e0125230. doi: 10.1371/journal.pone.0125230. eCollection 2015.
8
Survey on Monitoring and Quality Controlling of the Mobile Biosignal Delivery.移动生物信号传输的监测与质量控制调查
Interdiscip Sci. 2019 Jun;11(2):307-319. doi: 10.1007/s12539-017-0263-2. Epub 2017 Oct 31.
9
A cross-layer adaptation scheme for improving IEEE 802.11e QoS by learning.一种通过学习来改进IEEE 802.11e服务质量的跨层自适应方案。
IEEE Trans Neural Netw. 2006 Nov;17(6):1661-5. doi: 10.1109/TNN.2006.883014.
10
Providing QoS through machine-learning-driven adaptive multimedia applications.通过机器学习驱动的自适应多媒体应用程序提供QoS。
IEEE Trans Syst Man Cybern B Cybern. 2004 Jun;34(3):1398-411. doi: 10.1109/tsmcb.2004.825912.