Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Enabling Heterogeneous Deterministic Networks with Smart Collaborative Theory

Full metadata record
DC Field Value Language
dc.contributor.authorSong, Fei-
dc.contributor.authorLi, Letian-
dc.contributor.authorYou, Ilsun-
dc.contributor.authorZhang, Hongke-
dc.date.accessioned2021-09-10T05:48:18Z-
dc.date.available2021-09-10T05:48:18Z-
dc.date.issued2021-05-
dc.identifier.issn0890-8044-
dc.identifier.issn1558-156X-
dc.identifier.urihttps://scholarworks.bwise.kr/sch/handle/2021.sw.sch/18854-
dc.description.abstractCoronavirus disease (COVID-19) has presented extremely harsh requirements on deterministic transmission capability within different communication networks. However, most existing solutions mainly focus on one specific homogeneous scenario, such as pure IP routers or classical medium access control bridges, which leads to many tough challenges in flexibility and scalability. In this article, we propose a framework for heterogeneous deterministic networks (HDNs) to offer low latency and high reliability in tackling epidemics based on smart collaborative theory. Various wired and wireless connecting patterns are supported by utilizing a hybrid mode for COVID-19 relevant operations. Components generated from deterministic networking, time-sensitive networks, and 5G systems have been integrated to achieve corresponding features. The pervasive function translators are available according to virtualization technologies. The protocol-independent and segment-based concepts have been well considered and successfully implemented during our design process. The validations executed on top of the prototype and simulation platform illustrate the advantages of HDN. We aim to enable HDN as an evolutional structure for information exchange in eHealth and other vertical industries.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.titleEnabling Heterogeneous Deterministic Networks with Smart Collaborative Theory-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/MNET.2021.9454596-
dc.identifier.wosid000665641800011-
dc.identifier.bibliographicCitationIEEE Network, v.35, no.3, pp 64 - 71-
dc.citation.titleIEEE Network-
dc.citation.volume35-
dc.citation.number3-
dc.citation.startPage64-
dc.citation.endPage71-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Hardware & Architecture-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordAuthorCOVID-19-
dc.subject.keywordAuthorWireless communication-
dc.subject.keywordAuthor5G mobile communication-
dc.subject.keywordAuthorPandemics-
dc.subject.keywordAuthorTelemedicine-
dc.subject.keywordAuthorScalability-
dc.subject.keywordAuthorCollaboration-
Files in This Item
There are no files associated with this item.
Appears in
Collections
ETC > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE