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.
@article{arxiv.2007.11705,
title = {Event-based Detection of Changes in IaaS Performance Signatures},
author = {Sheik Mohammad Mostakim Fattah and Athman Bouguettaya},
journal= {arXiv preprint arXiv:2007.11705},
year = {2020}
}
Comments
8 pages, Accepted and to appear in 2020 International Conference on Services Computing (IEEE SCC 2020). Content may change prior to final publication