  We propose a novel ECA approach to manage changes in IaaS performance
signatures. The proposed approach relies on the detection of anomalous
performance behavior in the context of IaaS performance signatures. A novel
anomaly-based event detection technique is proposed. It utilizes the experience
of free trial users to detect potential changes in IaaS performance signatures.
A signature change detection technique is proposed using the cumulative sum
control chart analysis. Additionally, a self-adjustment method is introduced to
improve the accuracy of the proposed approach. A set of experiments based on
real-world datasets are conducted to show the effectiveness of the proposed
approach.
