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Organic Computing - Addressing Complexity by Controlled Self-Organization


Organic Computing - Addressing Complexity by Controlled Self-Organization



Published: 2006 November
Herausgeber: Tiziana Margaria, Anna Philippou, and Bernhard Steffen
Buchtitel: Post-Conference Proceedings of the 2nd International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (ISoLA 2006)
Seiten: 185-191
Verlag: IEEE

Referierte Veröffentlichung

BibTeX

Kurzfassung
In the past, the focus of the computer industry has been to improve hardware performance and add more and more features to the software. As a result, more and more appliances surrounding us are equipped with embedded computational power and wireless communication. As such, they become ever more flexible and multifunctional, and almost indispensable in daily life. On the other hand, the resulting systems become increasingly complex and unreliable, posing new challenges to designer and user.

Organic Computing (OC) has the vision to address the challenges of complex distributed systems by making them more life-like (organic), i.e. endowing them with abilities such as self-organization, self-configuration, self-repair, or adaptation. The designer's task is simplified, because it is no longer necessary to exactly specify the low-level system behavior in all possible situations that might occur, but instead leaving the system with a certain degree of freedom which allows it to react in an intelligent way to new situations. Also, use of such systems is simplified, as they can be controlled by setting few high-level goals, rather than having to manipulate many low-level parameters with unclear influence.

In this paper, we give a general introduction to OC, and propose a generic observer-controller architecture as a framework for designing OC systems. Then, it is shown how to use this architecture at the example of a traffic light controller. The paper concludes with a summary and a discussion of future challenges.

DOI Link: 10.1109/ISoLA.2006.19

Projekt

OTCOTC2QE



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Organic Computing