Industry 4.0 is characterized by the unprecedented connection by the Internet of things, Internet of Services, and called cyber-physical system (CPS), which can be considered systems that bring the physical world and the cyber space together.
CPS is defined as engineered systems that are built from and depend upon the synergy of computational and physical components. CPS has attracted a lot of research attention and many CPS-based applications have been built, such as smart healthcare, smart transportation, smart city, cyber-physical vehicle tracking system, etc.
CPSs have two parallel networks to control, namely a physical network of interconnected components of the infrastructure and a cyber-network comprised of intelligent controllers and the communication links among them. CPSs are able to interact with their environment via sensors and actuators. CPSs are expected to enable factories to organize and control themselves autonomously in a decentralized fashion and in real time. These factories are often referred to as smart factories.
The analysis of process history data by the product lifecycle requires new architectures and platforms for dealing with the enormous volume of data of great variation and fast speed. These drive the conventional data ingestion and storage to their limits, so Big Data platforms are needed.
Cloud computing infrastructure can serve as an effective platform for data storage required to perform big data analysis. Cloud computing not only provides facilities for the computation and processing of big data but also serves as a service model.
Kim Ryo Chol, a section head at the Faculty of Information Science and Technology, has proposed a big data aggregation and analysis system model for industrial cyber-physical system and its implementation in cloud computing environment. First, he explored a closed-loop cyber physical system model based on the big data ingestion and analysis system that provides optimization feedback. Second, he proposed an architecture of big data ingestion and analysis system and a vSphere-based private method of cloud environment configuration for its implementation.
He examined the data read performance of the proposed method compared with a traditional database. The experimental results show that the proposed architecture is faster than the one based on MySQL in terms of data processing time.
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