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Mapping biological systems to networ...

Rathore, Heena.

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Mapping biological systems to network systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mapping biological systems to network systems/ by Heena Rathore.
作者:	Rathore, Heena.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	ix, 196 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Computer networks - Design and construction. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-29782-8
ISBN:	9783319297828$q(electronic bk.)

Mapping biological systems to network systems
Rathore, Heena.

Mapping biological systems to network systems[electronic resource] /by Heena Rathore. - Cham :Springer International Publishing :2016. - ix, 196 p. :ill., digital ;24 cm.

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.

ISBN: 9783319297828$q(electronic bk.)

Standard No.: 10.1007/978-3-319-29782-8doiSubjects--Topical Terms:

599911
Computer networks
--Design and construction.

LC Class. No.: TK5105.5

Dewey Class. No.: 004.6

Mapping biological systems to network systems
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245 1 0 $a Mapping biological systems to network systems $h [electronic resource] / $c by Heena Rathore.
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505 0 $a 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.
520 $a 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.
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