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Research on Key Technology and Application of Big Data Integrated Machine

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International Conference on Applications and Techniques in Cyber Security and Intelligence ATCI 2018 (ATCI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 842))

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Abstract

In recent years, China’s big data industry has already had a good foundation and faced with a rare opportunity for development. This paper analyzes and compares the current situation of big data integrated products at home and abroad, and summarizes the key technologies of big data integrated machine. In view of the imperfect support system of large data industry in China, the problem of security and development of information security system has not been established, and a large data machine based on domestic chip is studied and proposed, and the related hardware, software and application demonstration are introduced in detail, in order to solve the massive storage, continuous expansion, and Yun Wei. Deployment, data personalized processing and other problems. By comparing the research and design of large data machine at home and abroad, the large data machine based on domestic chip has the characteristics of data processing security, high concurrent processing efficiency and stable operation.

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Acknowledgements

This work was supported by grants from The National Natural Science Foundation of China (No. 61502343), the Guangxi Natural Science Foundation (No. 2017GXNSFAA198148, 2015GXNSFBA139262) foundation of Wuzhou University(No. 2017B001), Guangxi Colleges and Universities Key Laboratory of Professional Software Technology, Wuzhou University.

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Correspondence to Ming Zheng .

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Zheng, M., Zhuo, M. (2019). Research on Key Technology and Application of Big Data Integrated Machine. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Security and Intelligence ATCI 2018. ATCI 2018. Advances in Intelligent Systems and Computing, vol 842. Springer, Cham. https://doi.org/10.1007/978-3-319-98776-7_134

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