Paper
25 May 2023 A survey on correlation and its structural analysis method for failure factors in cloud service
Fu Liao, Huang Liang, Chengling Huang, Xiaojian Li, Mingzhi Huang, Dandan Huang, Junxian Fan
Author Affiliations +
Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 1271204 (2023) https://doi.org/10.1117/12.2679292
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China
Abstract
Failure correlation is a necessary condition for source trace and violations determination in accountability of cloud services. This paper surveys the failure correlation. Most studies were involved in the correlation between services violation and failure factors only. However, an understanding of the correlation between the factors, the integrality of the factors is ambiguous and even few involve the correlation patterns of specific violations. Above all, the taxonomy of the failure factors, the methods of structure representation and analysis, some problems of recent research and suggestions are proposed in our paper.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fu Liao, Huang Liang, Chengling Huang, Xiaojian Li, Mingzhi Huang, Dandan Huang, and Junxian Fan "A survey on correlation and its structural analysis method for failure factors in cloud service", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 1271204 (25 May 2023); https://doi.org/10.1117/12.2679292
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KEYWORDS
Failure analysis

Clouds

Analytical research

Structural analysis

Factor analysis

Neural networks

Deep learning

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