Intelligent Reconfigurable Method of Cloud Computing Resources for Multimedia Data Delivery
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Junho | - |
dc.contributor.author | Choi, Chang | - |
dc.contributor.author | Yim, Kangbin | - |
dc.contributor.author | Kim, Jeongnyeo | - |
dc.contributor.author | Kim, Pankoo | - |
dc.date.accessioned | 2021-08-12T02:25:11Z | - |
dc.date.available | 2021-08-12T02:25:11Z | - |
dc.date.issued | 2013 | - |
dc.identifier.issn | 0868-4952 | - |
dc.identifier.issn | 1822-8844 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/14565 | - |
dc.description.abstract | While users increasingly use such large multimedia data, more people use the cloud computing technology. It is necessary to manage large data in an efficient way, and to consider transmission efficiency for multimedia data of different quality. To this end, an important thing is to ensure efficient distribution of important resources (CPU, network and storage) which constitute cloud computing, and variable distribution algorithms are required therefor. This study proposes a method of designing a scheme for applying MapReduce of the FP-Growth algorithm which is one of data mining methods based on the Hadoop platform at the stage of IaaS (Infrastructure As a Service) including CPU, networking and storages. The method is then for allocating resources with the scheme. | - |
dc.format.extent | 14 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Lithuanian Academy of Sciences | - |
dc.title | Intelligent Reconfigurable Method of Cloud Computing Resources for Multimedia Data Delivery | - |
dc.type | Article | - |
dc.publisher.location | 리투아니아 | - |
dc.identifier.scopusid | 2-s2.0-84897968877 | - |
dc.identifier.wosid | 000325443700003 | - |
dc.identifier.bibliographicCitation | Informatica, v.24, no.3, pp 381 - 394 | - |
dc.citation.title | Informatica | - |
dc.citation.volume | 24 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 381 | - |
dc.citation.endPage | 394 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Applied | - |
dc.subject.keywordPlus | MAP-REDUCE | - |
dc.subject.keywordPlus | MAPREDUCE | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | cloud computing | - |
dc.subject.keywordAuthor | mapreduce | - |
dc.subject.keywordAuthor | fp-growth algorithm | - |
dc.subject.keywordAuthor | resource provisioning | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(31538) 22, Soonchunhyang-ro, Asan-si, Chungcheongnam-do, Republic of Korea+82-41-530-1114
COPYRIGHT 2021 by SOONCHUNHYANG UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.