Organic Computing is a form of biologically-inspired computing with organic properties. It has emerged recently as a challenging vision for future information processing systems. Organic Computing is based on the insight that we will soon be surrounded by large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicate freely, and organise themselves in order to perform the actions and services that seem to be required. The presence of networks of intelligent systems in our environment opens fascinating application areas but, at the same time, bears the problem of their controllability. Hence, we have to construct such systems — which we increasingly depend on — as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation towards human needs as opposed to a pure implementation of the technologically possible seems absolutely central. In order to achieve these goals, our technical systems will have to act more independently, flexibly, and autonomously, i.e. they will have to exhibit life-like properties. We call those systems "organic". Hence, an "Organic Computing System" is a technical system, which adapts dynamically to the current conditions of its environment. It is characterised by the self-X properties:
- self-organisation,
- self-configuration (auto-configuration),
- self-optimisation (automated optimization),
- self-healing,
- self-protection (automated computer security),
- self-explaining,
- and context-awareness.
The vision of Organic Computing and its fundamental concepts arose independently in different research areas like Neuroscience, Molecular Biology, and Computer Engineering. Self-organising systems have been studied for quite some time by mathematicians, sociologists, physicists, economists, and computer scientists, but so far almost exclusively based on strongly simplified artificial models. Central aspects of Organic Computing systems have been and will be inspired by an analysis of information processing in biological systems.
Contents |
Current research
First steps towards adaptive and self-organising computer systems are already being undertaken. Current research topics include: Adaptivity, reconfigurability, emergence of new properties, and self-organisation. In a variety of research projects the priority research program SPP 1183 of the German Research Foundation (DFG) addresses fundamental challenges in the design of Organic Computing systems; its objective is a deeper understanding of emergent global behaviour in self-organising systems and the design of specific concepts and tools to support the construction of Organic Computing systems for technical applications.
See also
References
- Müller-Schloer, Christian; v.d. Malsburg, Christoph and Würtz, Rolf P. Organic Computing. Aktuelles Schlagwort in Informatik Spektrum (2004) pp. 332-336.
- Müller-Schloer, Christian. Organic Computing – On the Feasibility of Controlled Emergence. CODES + ISSS 2004 Proceedings (2004) pp 2-5, ACM Press, ISBN 1-58113-937-3.
- Rochner, Fabian and Müller-Schloer, Christian. Emergence in Technical Systems. it Special Issue on Organic Computing (2005) pp. 188-200, Oldenbourg Verlag, Jahrgang 47, ISSN 1611-2776.
- Schmeck, Hartmut. Organic Computing – A New Vision for Distributed Embedded Systems. Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC’05) (2005) pp. 201-203, IEEE, IEEE Computer Society 2005.
- The portable UNIX programming system (PUPS) and CANTOR: a computational envorionment for dynamical representation and analysis of complex neurobiological data, Mark A O'Neill, and Claus-C Hilgetag, Phil Trans R Soc Lond B 356 (2001), 1259-1276
