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.

翻译：我们提出了一种新颖的变化检测框架，用于识别IaaS服务长期性能行为中的变化。IaaS服务的长期性能行为通过IaaS性能签名来表示。该框架利用时间序列相似性度量和滑动窗口技术来检测IaaS性能签名的变化。我们引入了一种新的IaaS性能噪声模型，使该框架能够区分性能噪声与实际的性能变化。当存在关于性能噪声的先验知识时，该框架采用一种新颖的基于信噪比（SNR）的方法来检测变化。通过使用真实世界数据集进行一系列实验，验证了所提变化检测框架的有效性。