State of the Art in Architectures for Self-aware Computing Systems



In this chapter, we review the state of the art in self-aware computing systems with a particular focus on software architectures. Therefore, we compare existing approaches targeting computing systems with similar characteristics as self-aware systems to the architectural concepts for single and collective self-aware systems discussed in the previous chapters. These approaches are particularly reference architectures and architectural frameworks and languages. Based on this comparison, we discuss open challenges for architectures of self-aware computing systems.


Goal Model Architectural Style Reference Architecture Autonomic Computing Architectural Concept 
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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This chapter is the result of stimulating discussions among the authors and other participants, especially Paola Inverardi and Peter Lewis, during the seminar on Model-driven Algorithms and Architectures for Self-Aware Computing Systems at Schloss Dagstuhl in January 2015 (


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Hasso Plattner Institute for Software Systems Engineering at the University of PotsdamPotsdamGermany
  2. 2.Telécom ParisTech, Equipe S3, Department INFRESParisFrance
  3. 3.Tu DresdenDresdenGermany
  4. 4.Aston Institute for Systems AnalyticsAston UniversityBirminghamUK
  5. 5.University KasselKasselGermany
  6. 6.University of Würzburg, Department of Computer ScienceWürzburgGermany
  7. 7.Aerospace Integration Science Center, The Aerospace CorporationCaliforniaUSA

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