Abstract
Design decisions for complex, component-based systems impact multiple quality of service (QoS) properties. Often, means to improve one quality property deteriorate another one. In this scenario, selecting a good solution with respect to a single quality attribute can lead to unacceptable results with respect to the other quality attributes. A promising way to deal with this problem is to exploit multi-objective optimization where the objectives represent different quality attributes. The aim of these techniques is to devise a set of solutions, each of which assures a trade-off between the conflicting qualities. To automate this task, this paper proposes a combined use of analytical optimization techniques and evolutionary algorithms to efficiently identify a significant set of design alternatives, from which an architecture that best fits the different quality objectives can be selected. The proposed approach can lead both to a reduction of development costs and to an improvement of the quality of the final system. We demonstrate the use of this approach on a simple case study.
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Martens, A., Ardagna, D., Koziolek, H., Mirandola, R., Reussner, R. (2010). A Hybrid Approach for Multi-attribute QoS Optimisation in Component Based Software Systems. In: Heineman, G.T., Kofron, J., Plasil, F. (eds) Research into Practice – Reality and Gaps. QoSA 2010. Lecture Notes in Computer Science, vol 6093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13821-8_8
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DOI: https://doi.org/10.1007/978-3-642-13821-8_8
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