Research on unstructured data storage in large-scale grid edge cloud for cross-region networking

Xiang Huang; Zhenjie Lin; Lilin Chen; Wenpeng Wu; Xiaojing Liu

doi:10.1117/12.3024613

13 May 2024 Research on unstructured data storage in large-scale grid edge cloud for cross-region networking

Xiang Huang, Zhenjie Lin, Lilin Chen, Wenpeng Wu, Xiaojing Liu

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315905 (2024) https://doi.org/10.1117/12.3024613
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

The current conventional unstructured data storage methods for grid edge cloud mainly use distributed storage to realize the data storage, which leads to poor storage efficiency due to ignoring the fitness between data attributes and databases. In this regard, a large-scale grid edge cloud unstructured data storage method for cross-region networking is proposed. The features of the edge cloud unstructured data are extracted utilizing data fusion. Access interfaces are designed to connect the temporal database with other types of databases to build a multi-target database with higher adaptability, and the data storage network topology is designed. In the experiments, the storage performance of the designed storage method is tested. The final results can prove that the average response time of the system is shorter when the proposed method is used to store the edge cloud data, and it has a more desirable data storage performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiang Huang, Zhenjie Lin, Lilin Chen, Wenpeng Wu, and Xiaojing Liu "Research on unstructured data storage in large-scale grid edge cloud for cross-region networking", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315905 (13 May 2024); https://doi.org/10.1117/12.3024613

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