Integrating Run-Time Observations and Design Component Models for Cloud System Analysis.

Heinrich, Robert, Schmieders, Eric, Jung, Reiner, Rostami, Kiana, Metzger, Andreas, Hasselbring, Wilhelm, Reussner, Ralf and Pohl, Klaus (2014) Integrating Run-Time Observations and Design Component Models for Cloud System Analysis. [Paper] In: 9th Workshop on Models@run.time. , September 30, 2014, Valencia, Spain . Proceedings of the 9th Workshop on Models@run.time. ; pp. 41-46 . Workshop Proceedings, 1270 .

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Abstract

Run-time models have been proven beneficial in the past for predicting upcoming quality flaws in cloud applications. Observation approaches relate measurements to executed code whereas prediction models oriented towards design components are commonly applied to reflect reconfigurations in the cloud. Levels of abstraction differ between code observations and these prediction models. In this position paper, we address the specification of causal relations between observation data and a component-based run-time prediction model. We introduce a meta-model for observation data, based on which we propose a mapping language to (a) bridge divergent levels of abstraction and (b) trigger model updates.

Document Type: Conference or Workshop Item (Paper)
Keywords: Run-Time Observations, Design Component Models, Cloud Systems
Research affiliation: Kiel University > Software Engineering
Open Access Journal?: Yes
Publisher: CEUR
Date Deposited: 17 Oct 2014 12:36
Last Modified: 23 Sep 2019 23:10
URI: https://oceanrep.geomar.de/id/eprint/25829

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