Towards organic sensing systems - Dynamically reconfigurable mixed-signal electronics for adaptive sensing in organic computing systems

The information processing abilities and, in particular, the adaptation capability of natural nervous systems and brains are of continued attraction for researchers and practitioners in the field of computing systems. With increasing complexity of architectures and systems, life-like properties or features of living beings, such as e.g., self-configuration, -optimization, -healing, -repairing, or -protection, become mandatory for computing systems, to achieve viable and robust systems. As genuine neurocomputing approaches will not be amenable in a short- and even mid-term perspective, a new research field, denoted as organic computing, pioneered e.g. by C.v.d. Malsburg et al., is recently emerging. In some aspects organic computing systems can be seen as an intermediate step on the way to actual neural computing systems, mimicking biological evidence and brain-like computing on a different level of abstraction. With a strongly increasing number of sensor principles and technologies, e.g., from biosensors to sensors employing nano-technology, the demands on appropriate electronics for multi-sensor systems get more and more stringent. Flexibility as well as quality and reliability issues must be met. Clearly, features advocated for organic computing in general will be most attractive to be adapted to sensing systems. Complementing the exclusively digital activities of existing research programs, this paper deals with the conceptual extension of organic computing concepts to the small yet decisive analog and mixed-signal components in real-world computing systems with a particular focus on sensing systems. The concept and first results of organic sensing systems will be reported.