Edge Fusion of Intelligent Industrial Park Based on MatrixOne and Pravega

Jingwei Yan, Yitong Liu, Shuqi Qin, Yun Shen, Yu Teng, Hongwen Yang
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Abstract

As the real-time requirements for big data processing in intelligent industrial parks continue to improve and the demands become increasingly diverse, building a data transmission, computing and storage pipeline with good scalability, high real-time performance, and easy-to-use interface has become an important direction for building a big data ecosystem in the park. This paper proposes an edge fusion solution for intelligent industrial parks based on MatrixOne and Pravega, which realizes deep integration of transmission, computing, and storage for multimedia data at the edge, with high reliability, low latency, and easy scalability. Specifically, this paper first points out the disadvantages of traditional cloud-side collaboration deployment solutions in terms of transmission and storage. Then, aiming at the real-time requirement of streaming multimedia data, an edge fusion solution is proposed, focusing on the streaming processing and distributed storage at the edge. Finally, the feasibility of the scheme is verified through experimental deployment.
随着智能工业园区对大数据处理实时性要求的不断提高和需求的日益多样化,构建可扩展性好、实时性高、界面易用的数据传输、计算和存储管道已成为园区大数据生态系统建设的重要方向。本文提出了一种基于MatrixOne和Pravega的智能工业园区边缘融合解决方案,实现了多媒体数据在边缘传输、计算和存储的深度融合,具有高可靠性、低时延、易扩展性等特点。具体而言,本文首先指出了传统的云端协作部署方案在传输和存储方面的不足。然后,针对流多媒体数据的实时性要求,提出了一种边缘融合解决方案,重点研究了流处理和边缘分布式存储。最后,通过实验部署验证了方案的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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