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020			_a9789811696091
024	7		_a10.1007/978-981-16-9609-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5105.8857 _b2022 EB
100	1		_aQiu, Tie _0(orcid)0000-0003-2324-2523 _1https://orcid.org/0000-0003-2324-2523 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9684993
245	1	0	_aRobustness Optimization for IoT Topology _cby Tie Qiu, Ning Chen, Songwei Zhang
250			_aFirst edition 2022
264		1	_aSingapore _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIV, 214 páginas) _b1 ilustraciones
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_a1.Introduction -- 2.Preliminaries of robustness optimization -- 3.Robustness optimization based on self-organization -- 4.Evolution-based robustness optimization -- 5.Robustness optimization based on swarm intelligence -- 6.Robustness optimization based on multi-objective cooperation -- 7.Robustness optimization based on self-learning -- 8.Robustness optimization based on node self-learning -- 9.Future research directions.
520			_aThe IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network's performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking. The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking. This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
988			_aSpringer_Computer_2022
650		7	_2embne _9483083 _aInternet de los objetos
700	1		_aChen, Ning _0(orcid)0000-0001-6806-4287 _1https://orcid.org/0000-0001-6806-4287 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9684994
700	1		_aZhang, Songwei _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9684995
776	0	8	_iPrinted edition: _z9789811696084
776	0	8	_iPrinted edition: _z9789811696107
776	0	8	_iPrinted edition: _z9789811696114
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-9609-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b10/2022 _dz _eIG _zSI