000			04045nam a22003855i 4500
001			85618
003			ES-MaUEC
005			20240111050123.0
007			cr nn 008mamaa
008			160210s2016 gw | s |||| 0|eng d
020			_a9783319297828
040			_aES-MaUEC
050		4	_aTK5105.5 _bR384 2016 EB
082	0	4	_a621.382
100	1		_aRathore, Heena _998736 _0Local
245	1	0	_aMapping Biological Systems to Network Systems _cby Heena Rathore
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (IX, 196 p.) _b107 ilustraciones, 70 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aIntroduction: 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			_aThe book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems in 2013; 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 in 2013; which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time in 2013; 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 in 2013; 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.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aRedes informáticas _0comprobar BNE19900997487 _2embne _9141354
650		7	_aInteligencia artificial _0comprobar BNE19900997218 _2embne _9413115
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-29782-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai97833192i97828
907			_a.b12948962 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b11-05-17 _cm _dz _ek _feng _ggw _h0
945			_aTK5105.5 R384 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i1159228x _z06-04-17
999			_c85618 _d85618 _x1