Introduction: Bio-inspired Systems.- Computer Networks.- Inceptive
Finding.- Swarm Intelligence and Social Insects.- Immunology and Immune System.-
Information Epidemics and Social Networking.- Artificial Neural Networks.- Genetic
Algorithms.- Bio-inspired Software Defined Networking.- Case Study: Providing
Trust in Wireless Sensor Networks.- Bio-inspired Approaches in Various
Engineering Domain.
The book presents the challenges inherent in the
paradigm shift of network systems from static to highly dynamic distributed
systems – it proposes solutions that the symbiotic nature of biological systems
can provide into altering networking systems to adapt to these changes. The
author discuss how biological systems – which have the inherent capabilities of
evolving, self-organizing, self-repairing and flourishing with time – are
inspiring researchers to take opportunities from the biology domain and map them
with the problems faced in network domain. The book revolves around the central
idea of bio-inspired systems -- it begins by exploring why biology and computer
network research are such a natural match. This is followed by presenting a
broad overview of biologically inspired research in network systems -- it is
classified by the biological field that inspired each topic and by the area of
networking in which that topic lies. Each case elucidates how biological
concepts have been most successfully applied in various
domains. Nevertheless, it also presents a case study discussing the
security aspects of wireless sensor networks and how biological solution stand
out in comparison to optimized solutions. Furthermore, it also discusses novel
biological solutions for solving problems in diverse engineering domains such
as mechanical, electrical, civil, aerospace, energy and agriculture. The
readers will not only get proper understanding of the bio inspired systems but
also better insight for developing novel bio inspired solutions.
Shows how bio-inspired systems – which are
inherently robust, flexible and have high resilience towards critical errors --
hold immense potential for next generation network systems
Outlines computing and problem solving techniques
inspired by biological systems that can provide flexible, adaptable ways of
solving networking problems
Provides insights into how the study of
biological systems can make network systems more flexible, adaptable,
self-organized, self-aware, and self-sufficient