Wednesday, February 6, 2013

Five Misconceptions about Self-Organizing Systems

from W. Elmenreich, H. de Meer. Self-organizing networked systems for technical applications: A discussion on open issues:

 

Misconception #1: Self-organizing systems establish a class of systems

If a system is considered to be self-organizing or not depends mainly on the way how the system is observed, especially where the borderline between the observed system and its environment is drawn. C. Gershenson and F. Heylighen [1] propose the following perspective to overcome this problem: Instead of thinking of Self-Organizing Systems as an absolute class of systems, self-organization should be understood as a way of observing systems. Depending on the type of problem and the
desired solution, the way of observing a system as an Self-Organizing System can be beneficial or not.

 

Misconception #2: All Self-organizing systems are chaotic systems

There is a relation between chaos theory and self-organization in that a Self-Organizing System may show chaotic behavior, that is having critical turning points (also known as bifurcations) in the system behavior. However, a Self-Organizing System does not necessarily have to show such behavior. Instead, some Self-Organizing Systems also might approach their target state without a sensitive dependence on initial conditions.
Accordingly, a system with chaotic behavior may be built without employing the typical building blocks of Self-Organizing Systems such as distributed entities and local interactions.

 

Misconception #3: The emerging structure is a primary property of self-organizing systems

Self-Organizing Systems provide a powerful mechanism to create structure and patterns. This phenomenon can be observed in many physical and biological systems, such as the skin pigmentation of fish, the polygonal pattern of nest territories of fish such as Tilapia, or the cathedral-like buildings of termites.
However, the emerging pattern should not be seen as a primary property of an Self-Organizing System. There are Self-Organizing Systems, like homeostatic operational control in living beings, where such a structure is not present or is hidden from the observer. Thus, the emerging structure can be rather seen as a secondary property that indicate self-organization in many cases.

 

Misconception #4: Self-organizing systems are always based on evolutionary processes

Evolutionary processes, as best known from biological examples, are an iterative mechanism of change in the inherited traits of a population of organisms from one generation to the next. Evolutionary processes are driven by mutation, selection and recombination.
Many biological examples of self-organizing systems have emerged from an evolutionary process, which made the term self-organization connected to evolution. Thus, the connection of Self-Organizing Systems to evolutionary processes is not an obligatory one, since many non-biological examples of Self-Organizing Systems have developed without an evolutionary process, thus showing the possibility to design self-organizing without an evolutionary process.
However, an interesting research task for future technical systems arises in constructing Self-Organizing Systems, which implement an evolution of their local rules in order to adjust to new situations.

 

Misconception #5: Any self-organizing system will never need maintenance

Many Self-Organizing Systems show adaptive behavior, which means that they can operate well within a wide range of input parameters. However, that does not imply that a technical Self-Organizing System will have a low maintenance effort. Typically, a complex technical system that must operate over a considerable life time will require maintenance in order to provide its service during system lifetime.
It is an open question if maintenance of a technical system with self-organizing properties will be easier or more complicated to maintain than a traditionally designed technical application. On the one hand, properties like robustness might make it easier to replace parts of the system without disturbing the overall operation, on the other hand, diagnosis and maintenance of an Self-Organizing System might turn out to be more complex than in systems built following a more straightforward approach.


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