大规模工业物联网网络边缘实时分布式计算

Emmanuel A. Oyekanlu, K. Scoles
{"title":"大规模工业物联网网络边缘实时分布式计算","authors":"Emmanuel A. Oyekanlu, K. Scoles","doi":"10.1109/SERVICES.2018.00045","DOIUrl":null,"url":null,"abstract":"Low-cost, real-time digital signal processors (DSPs) embedded in generic Internet of Things (IoT) edge devices can make significant contributions to distributed edge computing for industrial IoT (IIoT) networks. The DSP considered in this paper is the Texas Instruments (TI) TMS320C28x DSP (C28x). At the edge of the network, the C28x is programmed using low-level Embedded C programming language to construct the Morlet wavelet. Our implementation at this layer is the first known construction of the Morlet wavelet for C28x DSP using Embedded C. At the fog layer, near the edge of the IoT network, where more computing resources exist, the wavelet is then convolved with healthcare (electrocardiogram) and electrical network signals, using Matlab to reduce signal noise, and to identify important parts of examined signals. Convolution results indicates that the distributed computing approach for low-cost generic devices considered in this paper is suitable for use in large IIoT networks","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Real-Time Distributed Computing at Network Edges for Large Scale Industrial IoT Networks\",\"authors\":\"Emmanuel A. Oyekanlu, K. Scoles\",\"doi\":\"10.1109/SERVICES.2018.00045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Low-cost, real-time digital signal processors (DSPs) embedded in generic Internet of Things (IoT) edge devices can make significant contributions to distributed edge computing for industrial IoT (IIoT) networks. The DSP considered in this paper is the Texas Instruments (TI) TMS320C28x DSP (C28x). At the edge of the network, the C28x is programmed using low-level Embedded C programming language to construct the Morlet wavelet. Our implementation at this layer is the first known construction of the Morlet wavelet for C28x DSP using Embedded C. At the fog layer, near the edge of the IoT network, where more computing resources exist, the wavelet is then convolved with healthcare (electrocardiogram) and electrical network signals, using Matlab to reduce signal noise, and to identify important parts of examined signals. Convolution results indicates that the distributed computing approach for low-cost generic devices considered in this paper is suitable for use in large IIoT networks\",\"PeriodicalId\":130225,\"journal\":{\"name\":\"2018 IEEE World Congress on Services (SERVICES)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE World Congress on Services (SERVICES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SERVICES.2018.00045\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE World Congress on Services (SERVICES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERVICES.2018.00045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

嵌入在通用物联网(IoT)边缘设备中的低成本、实时数字信号处理器(dsp)可以为工业物联网(IIoT)网络的分布式边缘计算做出重大贡献。本文考虑的DSP是德州仪器(TI)的TMS320C28x DSP (C28x)。在网络边缘,用底层嵌入式C语言对C28x进行编程,构造Morlet小波。我们在这一层的实现是使用嵌入式c为C28x DSP构建Morlet小波的第一个已知结构。在雾层,靠近物联网网络的边缘,存在更多的计算资源,然后将小波与医疗(心电图)和电子网络信号进行卷积,使用Matlab来降低信号噪声,并识别检测信号的重要部分。卷积结果表明,本文考虑的低成本通用设备的分布式计算方法适用于大型工业物联网网络
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Distributed Computing at Network Edges for Large Scale Industrial IoT Networks
Low-cost, real-time digital signal processors (DSPs) embedded in generic Internet of Things (IoT) edge devices can make significant contributions to distributed edge computing for industrial IoT (IIoT) networks. The DSP considered in this paper is the Texas Instruments (TI) TMS320C28x DSP (C28x). At the edge of the network, the C28x is programmed using low-level Embedded C programming language to construct the Morlet wavelet. Our implementation at this layer is the first known construction of the Morlet wavelet for C28x DSP using Embedded C. At the fog layer, near the edge of the IoT network, where more computing resources exist, the wavelet is then convolved with healthcare (electrocardiogram) and electrical network signals, using Matlab to reduce signal noise, and to identify important parts of examined signals. Convolution results indicates that the distributed computing approach for low-cost generic devices considered in this paper is suitable for use in large IIoT networks
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信