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001447622 001__ 1447622
001447622 003__ OCoLC
001447622 005__ 20230310004126.0
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001447622 020__ $$a9789811696091$$q(electronic bk.)
001447622 020__ $$a9811696098$$q(electronic bk.)
001447622 020__ $$z981169608X
001447622 020__ $$z9789811696084
001447622 0247_ $$a10.1007/978-981-16-9609-1$$2doi
001447622 035__ $$aSP(OCoLC)1331408583
001447622 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dOCLCQ
001447622 049__ $$aISEA
001447622 050_4 $$aTK5105.8857
001447622 08204 $$a004.678$$223/eng/20220621
001447622 1001_ $$aQiu, Tie,$$eauthor.
001447622 24510 $$aRobustness optimization for IoT topology /$$cTie Qiu, Ning Chen, Songwei Zhang.
001447622 264_1 $$aSingapore :$$bSpringer,$$c2022.
001447622 300__ $$a1 online resource (1 volume) :$$billustrations (black and white, and color).
001447622 336__ $$atext$$btxt$$2rdacontent
001447622 337__ $$acomputer$$bc$$2rdamedia
001447622 338__ $$aonline resource$$bcr$$2rdacarrier
001447622 504__ $$aIncludes bibliographical references.
001447622 5050_ $$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.
001447622 506__ $$aAccess limited to authorized users.
001447622 520__ $$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 networks 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.
001447622 588__ $$aDescription based on print version record.
001447622 650_0 $$aInternet of things.
001447622 655_0 $$aElectronic books.
001447622 7001_ $$aChen, Ning,$$eauthor.
001447622 7001_ $$aZhang, Songwei,$$eauthor.
001447622 77608 $$iPrint version:$$aQIU, TIE. CHEN, NING. ZHANG, SONGWEI.$$tROBUSTNESS OPTIMIZATION FOR IOT TOPOLOGY.$$d[Place of publication not identified] : SPRINGER VERLAG, SINGAPOR, 2022$$z981169608X$$w(OCoLC)1289480532
001447622 852__ $$bebk
001447622 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-9609-1$$zOnline Access$$91397441.1
001447622 909CO $$ooai:library.usi.edu:1447622$$pGLOBAL_SET
001447622 980__ $$aBIB
001447622 980__ $$aEBOOK
001447622 982__ $$aEbook
001447622 983__ $$aOnline
001447622 994__ $$a92$$bISE