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Model-Driven Assessment of QoS-Aware Self-Adaptation

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 5525)

Abstract

One of the main goals of a self-adaptable software system is to meet the required Quality of Service (QoS) by autonomously modifying its structure/behavior in response to changes in the supporting infrastructure and surrounding physical environment. A key issue in the design and development of such system is the assessment of their effectiveness, both in terms of their ability to meet the required QoS under different operating conditions, and in terms of the costs involved by the reconfiguration process, which could outweigh the benefit of the reconfiguration. This paper introduces an approach to support this assessment, with a focus on performance and dependability attributes. Our approach is based on the idea of defining a model transformation chain that maps a “design oriented” model of the system to an “analysis oriented” model that lends itself to the application of a suitable analysis methodology. We identify some key concepts that should be present in the design model of a dynamically adaptable system, and show how to devise a transformation from such a model to a target analysis models, focusing in particular on models of component or service oriented systems.

Keywords

  • Model Transformation
  • Network Traffic
  • Adaptable System
  • Service Level Agreement
  • Average Response Time

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Grassi, V., Mirandola, R., Randazzo, E. (2009). Model-Driven Assessment of QoS-Aware Self-Adaptation. In: Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds) Software Engineering for Self-Adaptive Systems. Lecture Notes in Computer Science, vol 5525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02161-9_11

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  • DOI: https://doi.org/10.1007/978-3-642-02161-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02160-2

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