Cross-room cluster fault detection for distributed storage based on improved Gaussian mixture modeling

Jiacheng Fu; Anni Huang; Junbing Pan; Xiaoying Mo; Miaoru Su

doi:10.1117/12.3051690

18 November 2024 Cross-room cluster fault detection for distributed storage based on improved Gaussian mixture modeling

Jiacheng Fu, Anni Huang, Junbing Pan, Xiaoying Mo, Miaoru Su

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134033E (2024) https://doi.org/10.1117/12.3051690
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

The cross server room cluster environment is prone to failures due to network latency, node failures and other factors. In order to ensure the smooth progress of fault detection in cross server room cluster environment, a distributed storage cross server room cluster fault detection method based on improved Gaussian mixture model is proposed. First, the data in the cluster is modeled by using GMM; second, the storage resources on multiple independent devices are integrated through the network to form a unified virtual storage device. Finally, according to the running environment of the application program and the current state of the network, the distributed storage cross server room cluster fault detection is dynamically adjusted to further improve the adaptive performance of the fault detector and the accuracy of the result determination. The feasibility and performance of the model are evaluated. The experimental results show that compared with the traditional fault detection model, the distributed storage cross-room cluster fault detection method based on improved Gaussian mixture model has significantly improved the reliability and effectiveness of storage cross-room cluster.

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

Citation Download Citation

Jiacheng Fu, Anni Huang, Junbing Pan, Xiaoying Mo, and Miaoru Su "Cross-room cluster fault detection for distributed storage based on improved Gaussian mixture modeling", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134033E (18 November 2024); https://doi.org/10.1117/12.3051690

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