摘要
工业物联网时序数据呈爆炸式增长,导致工业时序数据的存储与处理面临应用需求多样化、低成本存储、高并发写入、数据处理时效性与有效性等挑战.为解决上述挑战,本文拟对如下内容进行研究:通过对工业物联网时序数据采集-存储-查询-处理一体化协同机理、工业物联网-应用融合的工业时序数据分布式存储与处理方法、工业物联网数据管理开源软件生态系统的融入方法等关键科学问题的研究,形成新一代工业物联网时序数据管理的理论体系.围绕"端边云协同的工业物联网时序数据管理理论""新型工业时序数据存储与高鲁棒处理技术""工业物联网时序数据库管理系统原型研发及应用示范"等开展研究,旨在建立新一代工业物联网数据管理体系和应用方案、提升我国工业物联网软件平台自主研发能力,具有重要理论意义和工程应用价值.
Abstract
The explosive growth of industrial IoT time-series data presents significant challenges to its storage and processing of industrial time-series data,including diversified application requirements,low-cost storage,high concurrency writing,and the timeliness and effectiveness of data processing.To address the above challenges,this article intends to conduct research on key scientific issues such as the integrated collaborative mechanism for industrial IoT time-series data collection,storage,querying,and processing,the distributed storage and processing method of industrial IoT application fusion,and the integration method of open source software ecosystem for industrial IoT data management,aiming to establish a theoretical system for the management of next-generation industrial IoT time-series data.The research is centered on the theories of"End Edge Cloud Collaboration for Industrial IoT Time Series Data Management","New Industrial Time Series Data Storage and High Robust Processing Technologies",and"Prototype Development and Application Demonstration of Industrial IoT Time Series Database Management System",aiming to develop a new generation of industrial IoT data management system and application solutions,enhance China's independent research and development capabilities of industrial IoT software platforms,and provide important theoretical significance and engineering application value.
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