Power big data management analysis and service based on cloud computing

Jing Yang; Bo Peng; Hui Wang; Lihua Gong; Longzhu Zhu

doi:10.1117/12.2653739

27 September 2022 Power big data management analysis and service based on cloud computing

Jing Yang, Bo Peng, Hui Wang, Lihua Gong, Longzhu Zhu

Proceedings Volume 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022); 123461I (2022) https://doi.org/10.1117/12.2653739
Event: 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 2022, Kunming, China

Abstract

To improve the response time of the power big data management and control service, the paper builds a more flexible and diversified management service mode. It creates a stable and reliable processing environment, combines with cloud computing technology, and designs a power big data management analysis and service method. The management and control environment is preprocessed, and the hierarchical processing mechanism is constructed in combination with the cloud computing model. Based on this, the cloud computing integrated power big data management and control model is designed, and the cloud service processing is used to realize the management and control. The final test results show that compared with the traditional multi-dimensional power big data management test group and the traditional positioning power big data management test group, the response time of the management and control service are obtained by the cloud computing power. The Big Data Management test group designed in this paper is relatively short, which indicates that it has a better management effect for power big data and has important practical significance.

Citation Download Citation

Jing Yang, Bo Peng, Hui Wang, Lihua Gong, and Longzhu Zhu "Power big data management analysis and service based on cloud computing", Proc. SPIE 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 123461I (27 September 2022); https://doi.org/10.1117/12.2653739

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