基于边缘计算技术的普适生态监测应用研究

Di Zheng, Xianfeng Zhang, Lin Chen
{"title":"基于边缘计算技术的普适生态监测应用研究","authors":"Di Zheng, Xianfeng Zhang, Lin Chen","doi":"10.1109/EUC50751.2020.00014","DOIUrl":null,"url":null,"abstract":"With rapid development of intelligent ecological applications, higher requirements have been put forward for more intelligent ecological monitoring business and more intelligent ecological monitoring instruments. The instruments themselves are required to have more abundant data collection and uploading capabilities, and can be used for spot monitoring better. At the same time, the types of ecological monitoring instruments are very complex, their interface standards, data uploading ability and transmission protocol are also very different, so existing processing methods cannot meet the requirements well. Therefore, we have chosen edge computing to overcome this problem and construct the pervasive ecological monitoring system. In this paper, we have designed a set of edge computing services for universal intelligent ecological monitoring instruments access including edge nodes design as well as transmission protocol analysis, microservice running based on cloud platform and so on.","PeriodicalId":331605,"journal":{"name":"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research of pervasive ecological monitoring applications based on edge computing technologies\",\"authors\":\"Di Zheng, Xianfeng Zhang, Lin Chen\",\"doi\":\"10.1109/EUC50751.2020.00014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With rapid development of intelligent ecological applications, higher requirements have been put forward for more intelligent ecological monitoring business and more intelligent ecological monitoring instruments. The instruments themselves are required to have more abundant data collection and uploading capabilities, and can be used for spot monitoring better. At the same time, the types of ecological monitoring instruments are very complex, their interface standards, data uploading ability and transmission protocol are also very different, so existing processing methods cannot meet the requirements well. Therefore, we have chosen edge computing to overcome this problem and construct the pervasive ecological monitoring system. In this paper, we have designed a set of edge computing services for universal intelligent ecological monitoring instruments access including edge nodes design as well as transmission protocol analysis, microservice running based on cloud platform and so on.\",\"PeriodicalId\":331605,\"journal\":{\"name\":\"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)\",\"volume\":\"158 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EUC50751.2020.00014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUC50751.2020.00014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着智能生态应用的快速发展,对更智能的生态监测业务和更智能的生态监测仪器提出了更高的要求。要求仪器本身具有更丰富的数据采集和上传能力,能够更好地用于现场监测。同时,生态监测仪器的种类非常复杂,其接口标准、数据上传能力和传输协议也有很大差异,现有的处理方法不能很好地满足要求。因此,我们选择边缘计算来克服这一问题,构建普适生态监测系统。本文设计了一套面向智能生态监测仪器通用接入的边缘计算服务,包括边缘节点设计、传输协议分析、基于云平台的微服务运行等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research of pervasive ecological monitoring applications based on edge computing technologies
With rapid development of intelligent ecological applications, higher requirements have been put forward for more intelligent ecological monitoring business and more intelligent ecological monitoring instruments. The instruments themselves are required to have more abundant data collection and uploading capabilities, and can be used for spot monitoring better. At the same time, the types of ecological monitoring instruments are very complex, their interface standards, data uploading ability and transmission protocol are also very different, so existing processing methods cannot meet the requirements well. Therefore, we have chosen edge computing to overcome this problem and construct the pervasive ecological monitoring system. In this paper, we have designed a set of edge computing services for universal intelligent ecological monitoring instruments access including edge nodes design as well as transmission protocol analysis, microservice running based on cloud platform and so on.
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
期刊最新文献
Unit Testing Framework for Embedded Component Systems [Title page iii] Efficient Difference Analysis Algorithm for Runtime Requirement Degradation under System Functional Fault Converting Driving Scenario Framework for Testing Self-Driving Systems Research of pervasive ecological monitoring applications based on edge computing technologies
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1