Abstract
Monitoring the preservation of quality of service (QoS) properties during the operation of service-based systems at runtime is an important verification measure for determining whether current service usage is compliant with agreed SLAs. Monitoring, however, does not always provide sufficient scope for taking control actions against violations, as it only detects violations after they occur. This chapter describes a model-based prediction framework for detecting potential violations of QoS properties before they occur to enable the undertaking of control actions that could prevent the violations. EVEREST+ receives prediction specifications expressed in Event Calculus and automatically identifies relevant monitoring data that should be collected at runtime to infer QoS property prediction models. It then analyses runtime monitoring data to infer statistical prediction models for the relevant properties, and uses the models to detect potential violations of QoS properties and the probability of such violations.
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Lorenzoli, D., Spanoudakis, G. (2011). Runtime Prediction. In: Wieder, P., Butler, J., Theilmann, W., Yahyapour, R. (eds) Service Level Agreements for Cloud Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1614-2_9
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DOI: https://doi.org/10.1007/978-1-4614-1614-2_9
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