4 papers
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models
Wei Guan, Jian Cao, Jianqi Gao +2
Detecting anomalies in business processes is crucial for ensuring operational success. While many existing methods rely on statistical frequency to detect anomalies, it's important…
LogLLM: Log-based Anomaly Detection Using Large Language Models
Wei Guan, Jian Cao, Shiyou Qian +2
Software systems often record important runtime information in logs to help with troubleshooting. Log-based anomaly detection has become a key research area that aims to identify s…
Mitigating Interference of Microservices with a Scoring Mechanism in Large-scale Clusters
Dingyu Yang, Kangpeng Zheng, Shiyou Qian +2
Co-locating latency-critical services (LCSs) and best-effort jobs (BEJs) constitute the principal approach for enhancing resource utilization in production. Nevertheless, the co-lo…
Humas: A Heterogeneity- and Upgrade-aware Microservice Auto-scaling Framework in Large-scale Data Centers
Qin Hua, Dingyu Yang, Shiyou Qian +3
An effective auto-scaling framework is essential for microservices to ensure performance stability and resource efficiency under dynamic workloads. As revealed by many prior studie…