소장자료
| LDR | 03822nam a22005175i 4500 | ||
| 001 | 0100775398▲ | ||
| 003 | DE-He213▲ | ||
| 005 | 20231018103402▲ | ||
| 007 | cr nn 008mamaa▲ | ||
| 008 | 220610s2022 si | s |||| 0|eng d▲ | ||
| 020 | ▼a9789811696091▼9978-981-16-9609-1▲ | ||
| 024 | 7 | ▼a10.1007/978-981-16-9609-1▼2doi▲ | |
| 050 | 4 | ▼aTK5105.5-5105.9▲ | |
| 082 | 0 | 4 | ▼a004.6▼223▲ |
| 100 | 1 | ▼aQiu, Tie.▼eauthor.▼0(orcid)0000-0003-2324-2523▼1https://orcid.org/0000-0003-2324-2523▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
| 245 | 1 | 0 | ▼aRobustness Optimization for IoT Topology▼h[electronic resource] /▼cby Tie Qiu, Ning Chen, Songwei Zhang.▲ |
| 250 | ▼a1st ed. 2022.▲ | ||
| 264 | 1 | ▼aSingapore :▼bSpringer Nature Singapore :▼bImprint: Springer,▼c2022.▲ | |
| 300 | ▼aXIV, 214 p. 1 illus.▼bonline resource.▲ | ||
| 336 | ▼atext▼btxt▼2rdacontent▲ | ||
| 337 | ▼acomputer▼bc▼2rdamedia▲ | ||
| 338 | ▼aonline resource▼bcr▼2rdacarrier▲ | ||
| 347 | ▼atext file▼bPDF▼2rda▲ | ||
| 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.▲ | ||
| 650 | 0 | ▼aComputer networks .▲ | |
| 650 | 0 | ▼aArtificial intelligence.▲ | |
| 650 | 0 | ▼aElectronic digital computers—Evaluation.▲ | |
| 650 | 1 | 4 | ▼aComputer Communication Networks.▲ |
| 650 | 2 | 4 | ▼aArtificial Intelligence.▲ |
| 650 | 2 | 4 | ▼aSystem Performance and Evaluation.▲ |
| 700 | 1 | ▼aChen, Ning.▼eauthor.▼0(orcid)0000-0001-6806-4287▼1https://orcid.org/0000-0001-6806-4287▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
| 700 | 1 | ▼aZhang, Songwei.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
| 710 | 2 | ▼aSpringerLink (Online service)▲ | |
| 773 | 0 | ▼tSpringer Nature eBook▲ | |
| 776 | 0 | 8 | ▼iPrinted edition:▼z9789811696084▲ |
| 776 | 0 | 8 | ▼iPrinted edition:▼z9789811696107▲ |
| 776 | 0 | 8 | ▼iPrinted edition:▼z9789811696114▲ |
| 856 | 4 | 0 | ▼uhttps://doi.org/10.1007/978-981-16-9609-1▲ |
Robustness Optimization for IoT Topology[electronic resource]
자료유형
국외eBook
서명/책임사항
Robustness Optimization for IoT Topology [electronic resource] / by Tie Qiu, Ning Chen, Songwei Zhang.
판사항
1st ed. 2022.
형태사항
XIV, 214 p. 1 illus. online resource.
내용주기
1.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.
요약주기
The 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.
주제
ISBN
9789811696091
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