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Article type: Research Article
Authors: Tomforde, Sven; | Müller-Schloer, Christian
Affiliations: Universität Augsburg, Organic Computing Group, Eichleitnerstr. 30, 86159 Augsburg, Germany | Leibniz Universität Hannover, System and Computer Architecture Group, Appelstr. 4, 30167 Hannover, Germany. E-mail: cms@sra.uni-hannover.de
Note: [] Corresponding author. E-mail: sven.tomforde@informatik.uni-augsburg.de.
Abstract: Current research initiatives like Organic Computing (OC) and Intelligent Environments (IEs) aim at building technology-driven embedded systems that are aware of the conditions in the real world, derive plans of how to act, and pro-actively manipulate their environment to serve the user. As a result, novel systems according to these initiatives are characterised by a high degree of adaptivity, user-sensitivity, robustness and reliability. Adaptivity means that for such systems we defer a part of the design process from design time to runtime. Therefore, we need a runtime infrastructure, which takes care of runtime modifications. And we need a meta-design process responsible for the parametrisation of the runtime infrastructure. This article presents such a meta-design process to develop such systems in a unified way in order to handle the growing complexity in technical systems by focusing on adaptation and self-optimisation capabilities. A promising application for organic concepts and a large-scale testbed for IEs is the control of road traffic signals in urban areas. This article exemplarily applies the proposed design process to a traffic scenario and evaluates it in a realistic setting modelling the (football) stadium environment in Hannover, Germany. Thereby, the significant benefit of the adaptation component developed through the design process is demonstrated in terms of traffic-relevant metrics like delays and energy consumption.
Keywords: Organic computing, intelligent environments, design process, traffic control, self-adaptation
DOI: 10.3233/AIS-140252
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 6, no. 2, pp. 179-198, 2014
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