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arXiv · 2410.17623

Signature-based IaaS Performance Change Detection

Sheik Mohammad Mostakim Fattah·Athman Bouguettaya
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Abstract

We propose a novel change detection framework to identify changes in the long-term performance behavior of an IaaS service. An IaaS service's long-term performance behavior is represented by an IaaS performance signature. The proposed framework leverages time series similarity measures and a sliding window technique to detect changes in IaaS performance signatures. We introduce a new IaaS performance noise model that enables the proposed framework to distinguish between performance noise and actual changes in performance. The proposed framework utilizes a novel Signal-to-Noise Ratio (SNR) based approach to detect changes when prior knowledge about performance noise is available. A set of experiments is conducted using real-world datasets to demonstrate the effectiveness of the proposed change detection framework.

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Sheik Mohammad Mostakim Fattah, Athman Bouguettaya. 2024-10-23. Signature-based IaaS Performance Change Detection. https://doi.org/10.1145/3702228

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