Organic computing

Organic computing is a form of biologically-inspired computing with organic properties. It has emerged recently as a 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 new 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 lifelike properties. We call such systems "organic". Hence, an "Organic Computing System" is a technical system which adapts dynamically to exogenous and endogenous change. It is characterized by self-X or self-* properties:

The vision of Organic Computing and its fundamental concepts arose independently in different research areas like Neuroscience, Molecular Biology and Computer Engineering. It can be seen as an extension of the Autonomic computing vision of IBM.

Self-organizing 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. Organic computing can also be defined by biological processing systems. The ever expanding power of the processor(silicon based) will eventually hit a physical limit, due to the fact that you can make a, correctly functioning, silicon chip only so small. Using Organic compounds, not much different from the brain tissue that controls us, will be the only way to effectively continue growing our computing infrastructure in the future.

Self-* properties

There is a multitude of self-* properties. The top most so called CHOP (for Configuration, Healing, Organization and Protection) are extended by the self-explanation and context-awareness.

self-organization

Self-organization subsumes all other self-* properties, as they are all needed for a system to be self-organizing.

self-configuration

Self-configuration can be seen as the ability to set up the parameters of the system under study.

self-optimisation

Self-optimizing might be seen as the ability to search more efficient ways of solving problems. Automatic monitoring and control of resources to ensure the optimal functioning with respect to the defined requirements;

self-healing

Self-healing can be seen as the ability to recover from malfunctioning.

self-protection

Self-protection might be considered as a subproperty of self healing, but with the difference of protecting against malicious attacks.

self-explaining

Self-explanation represents the ability to communicate properties about oneself and one's abilities to others. There are two main areas of self-explanation:

Depending on the use case, self-explaining systems possess one or both of these self-explanatory properties.

context-awareness

Context-Awareness is the ability to react to endogenous and exogenous change in the system. It can be seen as a basis of adaptive systems.

Current research

First steps towards adaptive and self-organizing computer systems are already being undertaken.

Current research topics include: Adaptivity, reconfigurability, emergence of new properties, self-organization and self-explanation.

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 behavior in self-organizing systems and the design of specific concepts and tools to support the construction of Organic Computing systems for technical applications.

See also

References

External links