Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. The author of this book explores how bio-inspired methods can solve different problems linked to computer networks.
Future networks are expected to be autonomous, scalable and adaptive. During millions of years of evolution, nature has developed a number of different systems that present these and other characteristics required for the next generation networks. A series of bio-inspired methods have already been successfully used to solve the most diverse problems linked to computer networks. This book presents some of these techniques from a theoretical and practical point of view and provides a broad view of the field showing how different bio-inspired techniques are applied to computer networks.
It is aimed at network designers, system administrators, network researchers, graduate students and industrialists interested in the development of efficient solutions for distributed systems problems, as well as curious people interested in learning about biologically-inspired techniques
1. Evolution and Evolutionary Algorithms.
2. Chemical Computing.
3. Nervous System.
4. Swarm Intelligence (SI).
Daniel Camara is a Research Engineer at Telecom ParisTech, in France, currently working in the System on Chip Laboratory (LABSOC). His research interests include wireless networks, distributed systems, quality of software and artificial intelligence algorithms.
Table of Contents
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