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Using QoS-Contracts to Drive Architecture-Centric Self-adaptation

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6093))

Abstract

Self-adaptation is now a promising approach to maximize the satisfaction of requirements under changing environmental conditions. One of the key challenges for such self-adaptive systems is to automatically find a relevant architectural configuration. Existing approaches requires a set of adaptation strategies and the rough estimation of their side-effects. However, due to the lack of validation methods for such strategies and side-effects, existing approaches may lead to erroneous adaptations. Instead of side-effects, our solution leverages quality contracts whose accuracy can be separately established and which can be dynamically composed to get a quality prediction of any possible architectural configurations. To support self-adaptation, we propose a reactive planning algorithm which exploits quality contracts to dynamically discover unforeseen architectural configurations. We illustrate our approach using a running HTTP server adapting its architecture with respect to the number and the similarity of incoming requests.

This work is partially sponsored by the National Key Basic Research and Development Program of China under Grant No. 2009CB320703; the National Natural Science Foundation of China under Grant No. 60821003, 60873060; the High-Tech Research and Development Program of China under Grant No. 2009AA01Z16; and the EU FP7 under Grant No. 231167.

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Chauvel, F., Song, H., Chen, X., Huang, G., Mei, H. (2010). Using QoS-Contracts to Drive Architecture-Centric Self-adaptation. 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_9

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  • DOI: https://doi.org/10.1007/978-3-642-13821-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13820-1

  • Online ISBN: 978-3-642-13821-8

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