Interdisciplinary issues for the management of next generation autonomic wireless systems: nature-inspired techniques and organic computing

Abstract

Next generation communication systems have become a hot research issue in these last few years. For an efficient management of these networks, multidisciplinary knowledge and cooperation between different research fields is important. In particular, the next generation of wireless systems needs to satisfy some self-properties such as self-describing, self-organising, self-managing, self-configuring, self-optimising, self-monitoring, self-adapting and self-healing. In order to provide these features traditional approaches cannot be employed, owing to the computing complexity involved, so new solutions must be considered. The most suitable techniques to solve the above-mentioned issues is certainly organic computing and nature inspired techniques. Therefore, the main goal of our work is to provide a description of the principal characteristics of these new kinds of network and an overview in the various nature-inspired and organic computing techniques such as the neural network, molecular computing, Cellular Automata (CA), Genetic Algorithms (GAs), epidemic propagation strategies and finally, Swarm Intelligence (SI).