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Cited 13 time in webofscience Cited 26 time in scopus
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A Centralised Cloud Services Repository (CCSR) Framework for Optimal Cloud Service Advertisement Discovery From Heterogenous Web Portals

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dc.contributor.authorAlkalbani, Asma Musabah-
dc.contributor.authorHussain, Walayat-
dc.contributor.authorKim, Jung Yoon-
dc.date.available2020-02-27T07:43:13Z-
dc.date.created2020-02-05-
dc.date.issued2019-
dc.identifier.issn2169-3536-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/2908-
dc.description.abstractA cloud service marketplace is the first point for a consumer to discovery, select and possible composition of different services. Although there are some private cloud service marketplaces, such as Microsoft Azure, that allow consumers to search service advertainment belonging to a given vendor. However, due to an increase in the number of cloud service advertisement, a consumer needs to find related services across the worldwide web (WWW). A consumer mostly uses a search engine such as Google, Bing, for the service advertisement discovery. However, these search engines are insufficient in retrieving related cloud services advertainments on time. There is a need for a framework that effectively and efficiently discovery of the related service advertisement for ordinary users. This paper addresses the issue by proposing a user-friendly harvester and a centralised cloud service repository framework. The proposed Centralised Cloud Service Repository (CCSR) framework has two modules - Harvesting as-a-Service (HaaS) and the service repository module. The HaaS module allows users to extract real-time data from the web and make it available to different file format without the need to write any code. The service repository module provides a centralised cloud service repository that enables a consumer for efficient and effective cloud service discovery. We validate and demonstrate the suitability of our framework by comparing its efficiency and feasibility with three widely used open-source harvesters. From the evaluative result, we observe that when we harvest a large number of services advertisements, the HaaS is more efficient compared with the traditional harvesting tools. Our cloud services advertisements dataset is publicly available for future research at: http://cloudmarketregistry.com/cloud-market-registry/home.html.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.relation.isPartOfIEEE ACCESS-
dc.subjectOF-THE-ART-
dc.subjectSELECTION METHOD-
dc.subjectCHECKING-
dc.titleA Centralised Cloud Services Repository (CCSR) Framework for Optimal Cloud Service Advertisement Discovery From Heterogenous Web Portals-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000487233800005-
dc.identifier.doi10.1109/ACCESS.2019.2939543-
dc.identifier.bibliographicCitationIEEE ACCESS, v.7, pp.128213 - 128223-
dc.identifier.scopusid2-s2.0-85078044950-
dc.citation.endPage128223-
dc.citation.startPage128213-
dc.citation.titleIEEE ACCESS-
dc.citation.volume7-
dc.contributor.affiliatedAuthorKim, Jung Yoon-
dc.type.docTypeArticle-
dc.subject.keywordAuthorCloud services discovery-
dc.subject.keywordAuthorweb harvesting-
dc.subject.keywordAuthorservice advertisements-
dc.subject.keywordAuthorontology-
dc.subject.keywordAuthorcentralized repository-
dc.subject.keywordAuthorheterogeneous data-
dc.subject.keywordPlusOF-THE-ART-
dc.subject.keywordPlusSELECTION METHOD-
dc.subject.keywordPlusCHECKING-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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College of IT Convergence (Department of Game Media)
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