Abstract
Describing, understanding, and modeling the behavior of systems built upon self-organizing principles (such as many bio-inspired systems) is key to engineering self-organizing systems that can solve problems in real computing environments. Capturing the properties of the micro-macro linkage that connects local behaviors of system components to global emergent properties of the system as a whole is particularly important. Different kinds of models have been proposed, each focusing on a different aspect of the problem: descriptive models provide notations that support the design activity and the application of self-organzing principles; validation models allow formal examination of dynamic properties; and analytic models provide techniques for mathematical exploration of abstracted collective behaviors. Our goal is to identify and select the best tools available from these families, extend them where needed, and tie them together to support the creation and analysis of self-organized autonomic computing systems in an integrated way.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Snyder, P.L., Valetto, G. (2012). Design and Modeling for Self-organizing Autonomic Systems. In: Hart, E., Timmis, J., Mitchell, P., Nakamo, T., Dabiri, F. (eds) Bio-Inspired Models of Networks, Information, and Computing Systems. BIONETICS 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32711-7_26
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DOI: https://doi.org/10.1007/978-3-642-32711-7_26
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