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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/221449
- Statistical detection of QoS violations based on CUSUM control charts
- Amin, Ayman; Colman, Alan; Grunske, Lars
- Currently software systems operate in highly dynamic contexts, and consequently they have to adapt their behavior in response to changes in t heir contexts or/and requirements. Existing approaches trigger adaptations after detecting violations in quality of service (QoS) requirements by just comparing observed QoS values to predefined thresholds without, any statistical confidence or certainty. These threshold-based adaptation approaches may perform unnecessary adaptations, which can lead to severe shortcomings such as follow-up failures or increased costs. In this paper we introduce a statistical approach based on CUSUM control charts called AuDeQAV - Automated Detection of QoS Attributes Violations. This approach estimates at runtime a current status of the running system, and monitors its QoS attributes and provides early detection of violations in its requirements with a defined level of confidence. This enables timely intervention preventing undesired consequences from the violation or from inappropriate remediation. We validated our approach using a series of experiments and response time datasets from real-world web services.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies
- Proceedings of the Third Joint ACM/SPEC International Conference on Performance Engineering (ICPE 2012), Boston, United States, 22-25 April 2012, pp. 97-108
- Publication year
- Cumulative sum control charts; CUSUM control charts; QoS; QoS violation; Quality of Service; Runtime adaptation; Runtime monitoring
- 9781450312028, 1450312020
- Publisher URL
- Copyright © 2012 ACM.
- Peer reviewed