Towards accurate anomaly detection for cloud system via graph-enhanced contrastive learning

Towards accurate anomaly detection for cloud system via graph-enhanced contrastive learning

Abstract As a critical technology, anomaly detection ensures the smooth operation of cloud systems while maintaining the market competitiveness of cloud service providers. However, the resource data in real-world cloud systems is predominantly unannotated, leading to insufficient supervised signals...

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Bibliographic Details
Main Authors: Zhen Zhang, Zhe Zhu, Chen Xu, Jinyu Zhang, Shaohua Xu
Format: Article
Language:English
Published: Springer 2024-11-01
Series:Complex & Intelligent Systems
Subjects:
Cloud computing
Anomaly detection
Graph neural network
Contrastive learning
Linear attention mechanism
Online Access:https://doi.org/10.1007/s40747-024-01659-x

Internet

https://doi.org/10.1007/s40747-024-01659-x

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