Research on File Storage Access Strategy for Massive Devices in Power Internet of Things
Wenbin Wang, Jixin Hou, Qing Liu, Chen Liu, Qiao Zhu, Yunan Sun · 2024
In the power Internet of Things, massive devices generate a large number of small files, such as videos, images, audios, logs, texts, etc. Due to the large volume and variety of file data, existing storage systems face huge challenges. This article proposes a series of solutions to this problem, including device-oriented distributed file storage architecture and small file storage optimization strategies. In terms of storage architecture, an efficient distributed storage architecture is designed to balance storage loads and improve data access performance and system fault tolerance through reasonable metadata management and data management strategies. In terms of storage optimization strategies, methods such as small file merging and caching mechanism optimization are adopted. Through these strategies, storage space utilization is significantly improved, and I/O performance and system response speed are improved. Experimental results show that the storage architecture and optimization strategy proposed in this article are significantly better than traditional methods in terms of storage efficiency, data access performance, and system response speed. These strategies have demonstrated good feasibility and superiority in practical applications. The research results of this article are of great significance for improving the overall performance and stability of the Internet of Things system, and provide an efficient file storage solution for the power Internet of Things. Future research will further optimize the system architecture, improve its adaptability and scalability in a cloud-native environment, and promote the further development of the power Internet of Things.