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Heterogeneous Data Integration and Fusion System Based on Metadata Conflict Algorithms in USPIOT

机译:USPIOT中基于元数据冲突算法的异构数据集成与融合系统

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With the development of the Internet of Things, data islands and information redundancy which caused by massive heterogeneous data has become a challenge of many commercial applications and scientific research hot spots. First, we proposed and designed a MapReduce data integration and data fusion architecture, then, we established a stable information processing environment and a unified information retrieval interface for users, and then we analyzed MapReduce implementation processes, management processes, and the connection process. Meanwhile we proposed a conflict processing algorithms in processing heterogeneous redundant data problems by using metadata, and applied them to the processing of creating the virtual database using MapReduce technology, eliminating the redundant information to enhance the utilization of data space. Finally, we established the bench system to provide a unified heterogeneous data programming interface and memory management with heterogeneous data integration and fusion for users in our developed platform USPIOT (Ubiquitous Service Platform for Internet Of Things) and achieved better results.
机译:随着物联网的发展,由大量异构数据引起的数据岛和信息冗余已成为许多商业应用和科学研究热点的挑战。首先,我们提出并设计了MapReduce数据集成和数据融合架构,然后为用户建立了稳定的信息处理环境和统一的信息检索接口,然后对MapReduce的实现过程,管理过程和连接过程进行了分析。同时提出了一种使用元数据处理异构冗余数据问题的冲突处理算法,并将其应用于MapReduce技术创建虚拟数据库的处理中,消除了冗余信息,提高了数据空间的利用率。最后,我们建立了基准系统,在我们开发的平台USPIOT(物联网通用服务平台)中为用户提供统一的异构数据编程接口和内存管理,以及异构数据集成和融合功能,并取得了较好的效果。

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