Big Data for Cyber Physical Systems: An Analysis of Challenges, Solutions and Opportunities

A. Jara, D. Genoud, Yann Bocchi
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引用次数: 37

Abstract

Cyber-Physical Systems (CPS) covers from M2M and Internet of Things (IoT) communications, heterogeneous data integration from multiple sources, security / privacy and its integration into the cloud computing and Big Data platforms. The integration of Big Data into CPS solutions presents several challenges and opportunities. Big Data for CPS is not suitable with conventional solutions based on offline or batch processing. The interconnection with the real-world, in industrial and critical environments, requires reaction in real-time. Therefore, real-time will be a vertical requirement from communication to Big Data analytics. Big Data for CPS requires on the one hand, real-time streams processing for real-time control, and on the other hand, batch processing for modeling and behaviors learning. This paper describes the existing solutions and the pending challenges, providing some guidelines to address the challenges.
网络物理系统的大数据:挑战、解决方案和机遇分析
网络物理系统(CPS)涵盖M2M和物联网(IoT)通信、多源异构数据集成、安全/隐私及其与云计算和大数据平台的集成。将大数据集成到CPS解决方案中带来了一些挑战和机遇。CPS的大数据不适合基于离线或批量处理的传统解决方案。在工业和关键环境中,与现实世界的互连需要实时响应。因此,从通信到大数据分析,实时将是一个垂直需求。CPS的大数据一方面需要实时流处理来实现实时控制,另一方面需要批处理来实现建模和行为学习。本文描述了现有的解决方案和即将面临的挑战,并提供了一些应对挑战的指导方针。
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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