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Planning Self-adaption with Graph Transformations

  • Conference paper
Applications of Graph Transformations with Industrial Relevance (AGTIVE 2011)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7233))

Abstract

Self-adaptive systems autonomously adjust their behavior in order to achieve their goals despite changes in the environment and the system itself. Self-adaption is typically implemented in software and often expressed in terms of architectural reconfiguration. The graph transformation formalism is a natural way to model the architectural reconfiguration in self-adaptive systems. In this paper, we present (1) how we employ graph transformations for the specification of architectural reconfiguration and (2) how we transform graph transformations into actions of the Planning Domain Definition Language (PDDL) in order to use off-the-shelf tools for the computation of self-adaptation plans. We illustrate our approach by a self-healing process and show the results of a simulation case study.

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Author information

Authors and Affiliations

  1. Software Engineering Division, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden

    Matthias Tichy

  2. National Institute of Informatics (NII), Tokyo, Japan

    Benjamin Klöpper

Authors
  1. Matthias Tichy
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  2. Benjamin Klöpper
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Editor information

Editors and Affiliations

  1. Real-Time Systems Lab, Technische Universität Darmstadt, Merckstraße 25, 64283, Darmstadt, Germany

    Andy Schürr  & Gergely Varró  & 

  2. Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar tudósok krt. 2, 1117, Budapest, Hungary

    Dániel Varró

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Tichy, M., Klöpper, B. (2012). Planning Self-adaption with Graph Transformations. In: Schürr, A., Varró, D., Varró, G. (eds) Applications of Graph Transformations with Industrial Relevance. AGTIVE 2011. Lecture Notes in Computer Science, vol 7233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34176-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-34176-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34175-5

  • Online ISBN: 978-3-642-34176-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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