Detailed Information

Cited 6 time in webofscience Cited 6 time in scopus
Metadata Downloads

Human-intelligence workflow management for the big data of augmented reality on cloud infrastructure

Full metadata record
DC Field Value Language
dc.contributor.authorKim, Hyun-Woo-
dc.contributor.authorPark, Jong Hyuk-
dc.contributor.authorJeong, Young-Sik-
dc.date.accessioned2024-08-08T03:30:49Z-
dc.date.available2024-08-08T03:30:49Z-
dc.date.issued2018-03-01-
dc.identifier.issn0925-2312-
dc.identifier.issn1872-8286-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/16986-
dc.description.abstractHuman-intelligence workflow management (HIWM) is proposed as a means of dynamically distributing and processing storage work and calculating operations for fast augmented reality (AR) service provision on diverse smart mobile devices based on human behavior to apply the next generation web environments. In HIWM, pre-processing is performed to minimize service response time according to the definition of metadata and user requests for AR services. Basically, to process big data for AR services, a dynamic job distribution scheme is proposed based on the computing capacity of desktops constituting the cloud infrastructures. For final AR services by HIWM, the results of the evaluation of the performance of HIWM in relation to big data processing time are presented. The results show that processing time is 40.56% less than that of the existed methods in proportion to AR service requests. (c) 2017 Elsevier B.V. All rights reserved.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherELSEVIER SCIENCE BV-
dc.titleHuman-intelligence workflow management for the big data of augmented reality on cloud infrastructure-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.neucom.2017.04.082-
dc.identifier.scopusid2-s2.0-85036526636-
dc.identifier.wosid000424888300004-
dc.identifier.bibliographicCitationNEUROCOMPUTING, v.279, pp 19 - 26-
dc.citation.titleNEUROCOMPUTING-
dc.citation.volume279-
dc.citation.startPage19-
dc.citation.endPage26-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusVIRTUALIZATION-
dc.subject.keywordAuthorHuman-intelligence workflow management-
dc.subject.keywordAuthorBig data-
dc.subject.keywordAuthorCloud infrastructure-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

qrcode

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

Related Researcher

Researcher Jeong, Young Sik photo

Jeong, Young Sik
College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
Read more

Altmetrics

Total Views & Downloads

BROWSE