Mapping Biological Systems to Network Systems
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Beschreibung
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 systemsOutlines computing and problem solving techniques
inspired by biological systems that can provide flexible, adaptable ways of
solving networking problemsProvides insights into how the study of
biological systems canmake network systems more flexible, adaptable,
self-organized, self-aware, and self-sufficient
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 Includes supplementary material: sn.pub/extras
Autor*in
Heena Rathore
Themen in »Mapping Biological Systems to Network Systems«
Bio-Inspired Machine Learning Bio-inspired systems Biologically inspired research in network systems Computer network research Dynamic distributed systems Genetic Algorithms Networking systems Swarm intelligence Wireless sensor networks