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Bio-inspired Networking
- 1st Edition - August 19, 2015
- Imprint: ISTE Press - Elsevier
- Author: Daniel Câmara
- Language: English
- Hardback ISBN:9 7 8 - 1 - 7 8 5 4 8 - 0 2 1 - 8
- eBook ISBN:9 7 8 - 0 - 0 8 - 1 0 0 4 6 5 - 4
Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In… Read more
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Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore 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. Indeed, a series of bio-inspired methods have 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.
- Discusses the key concepts of bio-inspired networking to aid you in finding efficient networking solutions
- Delivers examples of techniques both in theoretical concepts and practical applications
- Helps you apply nature's dynamic resource and task management to your computer networks
Academics and students in the field of computer network engineering; researchers and network engineers
- Introduction
- I.1 Heuristics and metaheuristics
- I.2 Establish limits
- I.3 Complexity
- I.4 Heuristics and nature
- I.5 What to choose
- I.6 Complex systems
- I.7 Treating limitations
- I.8 Modeling biological systems
- I.9 Classification of biological systems
- I.10 Self-organization
- 1. Evolution and Evolutionary Algorithms
- Abstract
- 1.1 Brief introduction to evolution
- 1.2 Mechanisms of evolution
- 1.3 Artificial evolution
- 1.4 Applications on networks
- 2. Chemical Computing
- Abstract
- 2.1 Artificial chemistry
- 2.2 Applications on networks
- 3. Nervous System
- Abstract
- 3.1 Nervous system hierarchy
- 3.2 The neuron
- 3.3 The neocortex
- 3.4 Speed and capacity
- 3.5 Artificial neural networks
- 3.6 Applications on networks
- 4. Swarm Intelligence (SI)
- Abstract
- 4.1 Ant colony optimization
- 4.2 Applications on networks
- 4.3 Particle swarm optimization
- 4.4 Applications on networks
- Glossary
- Index
- Edition: 1
- Published: August 19, 2015
- Imprint: ISTE Press - Elsevier
- Language: English
DC
Daniel Câmara
Daniel Câmara 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.
Affiliations and expertise
Research engineer, Telecom ParisTech, FranceRead Bio-inspired Networking on ScienceDirect