Abstract
At present, enterprises need data for data analysis. They mostly use a kind of point-to-point data transmission form, which does not have regulation mechanism in the process. However, it has the problem of low data reliability, including two parts as follows: 1) Faulty sensor affects the collected data amount of the terminal server; 2) offensive data invade the data in transmission. In view of this, we propose the hierarchical private cloud architecture, including three aspects as follows. Firstly, we use distributed computing and virtualization capabilities of cloud computing to realize the hierarchical transmission of data. Secondly, through this mechanism of hierarchical transmission and classification algorithm of machine learning, we realize hierarchical filtering of offensive data. Finally, by combining hierarchical transmission mechanism with threshold value, classification algorithm, and limit tolerance mechanism, we regulate the data amount to monitor fault sensor in real time. Experiments are conducted to assess the proposed architecture's performance. The results show that each layer acts as a protective screen to counterattack the offensive data, which shows good robustness, real-time, and adaptive ability. Moreover, to compare with OM mode, the identification efficiency of fault sensor of TM mode is improved by 2 times. Also, TM mode improves 33.33% identification acuity, which is suitable for the enterprises that are mainly based on streaming computing. In summary, the hierarchical private cloud architecture achieves the filtering of offensive data and the real-time identification of faulty sensor, which guarantees the security, accuracy, and integrity of the data transmission process.
Highlights
The development of big data has facilitated various enterprises such as semiconductor fabrication plant, colored filter manufacture [1], casting production [2], and commodity sales because of the potential value of data
Enterprises mostly use a kind of point-to-point transmission method (PTPTM), which transmits data from collection points to terminal servers without regulation mechanisms in the process
SYSTEM MODEL This paper proposes the hierarchical private cloud architecture, which aims to achieve hierarchical transmission of data, hierarchical filtering of Ψ, and real-time monitoring of Fsensor
Summary
The development of big data has facilitated various enterprises such as semiconductor fabrication plant, colored filter manufacture [1], casting production [2], and commodity sales because of the potential value of data. Aims to block the offensive data according to their own Thirdly, by the combination of hierarchical transmission filtering abilities This architecture follows multiple mechanism, threshold value, classification algorithm, and calculation rules and regulation modes for fault sensors limit tolerance mechanism, the hierarchical private cloud monitoring. The data and real-time detection of fault sensors, which helps hierarchical private cloud architecture of semiconductor environment monitoring workers conduct data analysis fabrication plant is divided into three layers: production unit efficiently. By using different methods such as machine learning, fog computing, and platform monitoring, the accuracy of the obtained data is gradually improved None of these studies discuss the use of hierarchical transmission mechanism in data amount balance regulation and real-time monitoring of faulty sensors
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