{"title":"Survey of Time Series Data Processing in Industrial Internet","authors":"Miaoqiong Wang, Kai Wei, Chunyu Jiang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00151","DOIUrl":null,"url":null,"abstract":"This paper focuses on the processing requirements of time series data in industrial and IoT fields. The study of time series data processing in industry is continued for a long time, and a mature solution of using real-time/ historian database has been formed. However, with the new demand of Industrial Internet, old architectures are unable to fully support requirements (i.e., large amount and real-time analysis of industrial data). Meanwhile, a new architecture for processing real-time data in mobile Internet started to mature, this forms a solution called time-series database, which provides lots of new advantages. When we try to use a new technology to replace an old one, many aspects should be considered. This paper focuses on these challenges, starting with the demands of the industry, to analyze how to solve traditional problems with new technologies. This paper also analyzes the development trend of time series data processing and puts forward some general requirements for the application of new technology in the field of Industrial Internet, which lays a theoretical foundation for the application and development of basic technologies of Industrial Internet.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper focuses on the processing requirements of time series data in industrial and IoT fields. The study of time series data processing in industry is continued for a long time, and a mature solution of using real-time/ historian database has been formed. However, with the new demand of Industrial Internet, old architectures are unable to fully support requirements (i.e., large amount and real-time analysis of industrial data). Meanwhile, a new architecture for processing real-time data in mobile Internet started to mature, this forms a solution called time-series database, which provides lots of new advantages. When we try to use a new technology to replace an old one, many aspects should be considered. This paper focuses on these challenges, starting with the demands of the industry, to analyze how to solve traditional problems with new technologies. This paper also analyzes the development trend of time series data processing and puts forward some general requirements for the application of new technology in the field of Industrial Internet, which lays a theoretical foundation for the application and development of basic technologies of Industrial Internet.
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工业互联网中时间序列数据处理研究综述
本文主要研究工业和物联网领域对时间序列数据的处理需求。工业上对时间序列数据处理的研究持续了很长时间,已经形成了使用实时/历史数据库的成熟解决方案。然而,随着工业互联网的新需求,旧的架构已经无法完全支持需求(即海量、实时的工业数据分析)。与此同时,移动互联网中处理实时数据的新架构开始成熟,形成了一种称为时间序列数据库的解决方案,提供了许多新的优势。当我们试图用新技术取代旧技术时,应该考虑很多方面。本文针对这些挑战,从行业需求出发,分析如何用新技术解决传统问题。本文还分析了时间序列数据处理的发展趋势,提出了新技术在工业互联网领域应用的一般要求,为工业互联网基础技术的应用和发展奠定了理论基础。
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