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cs.LG2025
Improving Pattern Recognition of Scheduling Anomalies through Structure-Aware and Semantically-Enhanced Graphs
Ning Lyu, Junjie Jiang, Lu Chang +3
This paper proposes a structure-aware driven scheduling graph modeling method to improve the accuracy and representation capability of anomaly identification in scheduling behavior…
cs.LG2025
Graph Neural AI with Temporal Dynamics for Comprehensive Anomaly Detection in Microservices
Qingyuan Zhang, Ning Lyu, Le Liu +3
This study addresses the problem of anomaly detection and root cause tracing in microservice architectures and proposes a unified framework that combines graph neural networks with…
cs.LG2025
Multi-Objective Adaptive Rate Limiting in Microservices Using Deep Reinforcement Learning
Ning Lyu, Yuxi Wang, Ziyu Cheng +2
As cloud computing and microservice architectures become increasingly prevalent, API rate limiting has emerged as a critical mechanism for ensuring system stability and service qua…