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Adaptivity and Self-organisation in Organic Computing Systems

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Organic Computing — A Paradigm Shift for Complex Systems

Part of the book series: Autonomic Systems ((ASYS,volume 1))

Abstract

Organic Computing (OC) and other research initiatives like Autonomic Computing or Proactive Computing have developed the vision of systems possessing life-like properties: they self-organise, adapt to their dynamically changing environments, and establish other so-called self-x properties, like self-healing, self-configuration, self-optimisation, etc. What we are searching for in OC are methodologies and concepts for systems that allow to cope with increasingly complex networked application systems by introduction of self-x properties and at the same time guarantee a trustworthy and adaptive response to externally provided system objectives and control actions. Therefore, in OC we talk about controlled self-organisation.

Although the terms self-organisation and adaptivity have been discussed for years, we miss a clear definition of self-organisation in most publications, which have a technically motivated background.

In this article, we briefly summarise the state of the art and suggest a characterisation of (controlled) self-organisation and adaptivity that is motivated by the main objectives of the OC initiative. We present a system classification of robust, adaptable, and adaptive systems and define a degree of autonomy to be able to quantify how autonomously a system is working. The degree of autonomy distinguishes and measures external control which is exerted directly by the user (no autonomy) from internal control of a system which might be fully controlled by an Observer/Controller architecture that is part of the system (full autonomy). The quantitative degree of autonomy provides the basis for characterising the notion of controlled self-organisation. Furthermore, we discuss several alternatives for the design of organic systems.

© 2010 Association for Computing Machinery (ACM), Inc. Reprinted, with permission, from: Schmeck, H. et al. “Adaptivity and Self-organisation in Organic Computing Systems,” ACM Transactions on Autonomous and Adaptive Systems (TAAS), Vol. 5:3, doi:10.1145/1837909.1837911.

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Authors and Affiliations

  1. Institute AIFB, Karlsruhe Institute of Technology (KIT), Bldg. 05.20, 76128, Karlsruhe, Germany

    Hartmut Schmeck & Urban Richter

  2. Institute of Systems Engineering, Leibniz Universität Hannover, Appelstr. 4, 30167, Hannover, Germany

    Christian Müller-Schloer, Emre Çakar & Moez Mnif

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Correspondence to Christian Müller-Schloer .

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Editors and Affiliations

  1. , Institute for Systems Engineering, Leibniz Universität Hannover, Appelstr. 4, Hannover, 30167, Germany

    Christian Müller-Schloer

  2. , Institute AIFB, Karlsruhe Institute of Technology, Kaiserstr. 89, Karlsruhe, 76133, Germany

    Hartmut Schmeck

  3. , Department of Computer Science, Universität Augsburg, Universitätsstr. 6a, Augsburg, 86159, Germany

    Theo Ungerer

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Schmeck, H., Müller-Schloer, C., Çakar, E., Mnif, M., Richter, U. (2011). Adaptivity and Self-organisation in Organic Computing Systems. In: Müller-Schloer, C., Schmeck, H., Ungerer, T. (eds) Organic Computing — A Paradigm Shift for Complex Systems. Autonomic Systems, vol 1. Springer, Basel. https://doi.org/10.1007/978-3-0348-0130-0_1

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  • DOI: https://doi.org/10.1007/978-3-0348-0130-0_1

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