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Articles by Chengda Xu

Structure-Aware Unified Modeling for Root Cause Localization in Microservice Systems Using Multi-Source Observability Data

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By Zixiao Huang, Sijia Li, Chengda Xu
| Preprints.org
You are already at the latest version By decoupling services and enabling elastic deployment, microservice architecture improves system scalability and evolutionary capability. At the same time, it substantially increases operational complexity. Failures often exhibit cross service propagation and a mismatch between observed symptoms and underlying root causes.
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Deep Learning-Based Uncertainty-Driven Robust Time Series Forecasting for Backend Service Metrics

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By Sijia Li, Chengda Xu, Chi Zhang, Bolin Chen
| Preprints.org
Submitted: 28 January 2026 You are already at the latest version This study addresses the challenge of forecasting backend service metrics in highly dynamic and disturbed environments and proposes a robust time series prediction framework based on uncertainty estimation. The method first applies a multi-scale encoding structure to decompose and represent service metric sequences, allowing the model to capture mixed characteristics of trends, periodic patterns, and noise disturbances.
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Cost-TrustFL: Cost-Aware Hierarchical Federated Learning with Lightweight Reputation Evaluation across Multi-Cloud

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By Jinyu Chen, Zixiao Huang, Chi Zhang, Chengda Xu
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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