computing architecture
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2022 ◽  
Vol 27 (4) ◽  
pp. 751-759
Author(s):  
Xiangmin Ji ◽  
Baonan Wang ◽  
Feng Hu ◽  
Chao Wang ◽  
Huanguo Zhang

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Lei Zhang

In order to improve the multisource data-driven fusion effect in the intelligent manufacturing process of complex products, based on the proposed adaptive fog computing architecture, this paper takes into account the efficient processing of complex product intelligent manufacturing services within the framework and the rational utilization of fog computing layer resources to establish a fog computing resource scheduling model. Moreover, this paper proposes a fog computing architecture for intelligent manufacturing services for complex products. The architecture adopts a three-layer fog computing framework, which can reasonably provide three types of services in the field of intelligent manufacturing. In addition, this study combines experimental research to verify the intelligent model of this article and counts the experimental results. From the analysis of experimental data, it can be seen that the complex product intelligent manufacturing system based on multisource data driven proposed in this paper meets the data fusion requirements of complex product intelligent manufacturing.


2022 ◽  
Author(s):  
Zhe Bing ◽  
Xing Wang ◽  
Zhenliang Dong ◽  
Luobing Dong ◽  
Tao He

2021 ◽  
Vol 46 (4) ◽  
pp. 47-52
Author(s):  
Aya N. Elbedwehy ◽  
Mohy Eldin Abo-Elsoud ◽  
Ahmed Elnakib

2021 ◽  
Author(s):  
Masoud Nouripayam ◽  
Arturo Prieto ◽  
Vignajeth Kuttuva Kishorelal ◽  
Joachim Rodrigues

Author(s):  
Paola Y. Reyes-Delgado ◽  
Hector A. Duran-Limon ◽  
Manuel Mora ◽  
Laura C. Rodriguez-Martinez

2021 ◽  
Vol 2095 (1) ◽  
pp. 012046
Author(s):  
Gang Shi ◽  
Yuechen Yang

Abstract In the process of analysing and processing terminal sensor information, a large number of terminal sensors are needed to collect front-end information. These front-end data collection, analysis and processing require high real-time, and need the support of location aware mobile computing services. Traditional cloud computing architecture is not the best choice for service scenarios with high real-time requirements. The fog computing architecture is to extend cloud computing services to the edge of the sensor network, coupled with appropriate fitness algorithms, can effectively improve the information analysis and early warning response speed of the geological disaster information early warning system.


Author(s):  
De-gan Zhang ◽  
Chen-hao Ni ◽  
Jie Zhang ◽  
Ting Zhang ◽  
Peng Yang ◽  
...  

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