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CCoDaMiC: A framework for Coherent Coordination of Data Migration and Computation platforms

机译:CCODAMIC:数据迁移和计算平台相干协调的框架

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摘要

The amount of data generated by millions of connected IoT sensors and devices is growing exponentially. The need to extract relevant information from this data in modern and future generation computing system, necessitates efficient data handling and processing platforms that can migrate such big data from one location to other locations seamlessly and securely, and can provide a way to preprocess and analyze that data before migrating to the final destination. Various data pipeline architectures have been proposed allowing the data administrator/user to handle the data migration operation efficiently. However, the modern data pipeline architectures do not offer built-in functionalities for ensuring data veracity, which includes data accuracy, trustworthiness and security. Furthermore, allowing the intermediate data to be processed, especially in the serverless computing environment, is becoming a cumbersome task. In order to fill this research gap, this paper introduces an efficient and novel data pipeline architecture, named as CCoDaMiC (Coherent Coordination of Data Migration and Computation), which brings both the data migration operation and its computation together into one place. This also ensures that the data delivered to the next destination/pipeline block is accurate and secure. The proposed framework is implemented in private OpenStack environment and Apache Nifi.
机译:由数百万连接的物联网传感器和设备产生的数据量是指数增长的。需要在现代和未来的生成计算系统中提取来自此数据的相关信息,需要有效的数据处理和处理平台,可以无缝且安全地将这些大数据从一个位置迁移到其他位置,并且可以提供预处理和分析的方法迁移到最终目的地之前的数据。已经提出了各种数据管道架构,允许数据管理员/用户有效地处理数据迁移操作。但是,现代数据管道架构不提供内置功能,以确保数据准确性,包括数据准确性,可信度和安全性。此外,允许处理中间数据,尤其是在无服务器计算环境中,正在成为繁琐的任务。为了填补这一研究差距,本文介绍了一个名为CCODAMIC(数据迁移和计算的连贯协调)的高效和新的数据流水线架构,这将数据迁移操作及其计算在一起。这也可确保提供给下一个目的地/管道块的数据是准确和安全的。建议的框架是在私人OpenStack环境和Apache Nifi中实现的。

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