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- 저자 : Aitizaz Ali (검색결과 1 건)
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A machine learning framework for performance anomaly detection
Muhammad Hasnain,Muhammad Fermi Pasha,Imran Ghani,정승렬,Aitizaz Ali 한국인터넷정보학회 2022 인터넷정보학회논문지 Vol.23 No.2
Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.
ScienceON
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