A Cloud Repository and Discovery Framework Based on a Unified Business and Cloud Service Ontology

Tahamtan, Amirreza; Beheshti, Seyed Amir; Anjomshoaa, Amin; Tjoa, A. Min

doi:10.1109/services.2012.42

Cited by 43 publications

(32 citation statements)

References 13 publications

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“…4 demonstrate the extensions AoFeCSO achieved in contrast to other existing models (i.e. [8,9,10,11,12,31]). …”

Section: Agility-centric Designmentioning

confidence: 81%

“…While existing practices [4,9] utilize such for attributing cloud service characteristics, functional and nonfunctional properties, very few touches the details of how or how well those cloud services own these characteristics and properties. Fig.…”

Section: In-depth Cloud Service Object Property Assertionmentioning

confidence: 99%

“…Existing models [4,8,9,10,11,12,32] tend to ignore the many relationships among cloud computing concept. Firstly, the interoperability between CSPs and cloud services is often inexplicitly expressed.…”

Section: Explicit Cloud Service and Concept Relationship Assertionmentioning

confidence: 99%

“…III) The recommendation functions consider the fuzziness occurred in cloud service specifications; this enables a clearer view of the small differences between similar cloud services through more precise service recommendation ratios. Unified business and cloud service ontology [9] FCFA [10] CoCoOn [11] Cloud ontology [12] Cloud Ontology [32] Business ontology [56] AoFe-CSO IaaS cloud entities and properties Additionally, as Table 5 summarizes, the proposed approach is able to capture and present extended service specifications from a variety of aspects, e.g. to show multiple service model information, explaining granular details of service attributes, revealing service attribute connections, and processing fuzzy service specifications.…”

Section: Suitability For Service Retrieval and Recommendation Tasksmentioning

confidence: 99%

“…Particularly, research on cloud computing/service semantic modeling involves various ontological approaches, such as single ontology [9], multiple-layered ontologies [7] and multiple ontologies [10], etc. The semantic platform for cloud service annotation and retrieval [8] utilizes multiple ontologies of different domains.…”

Section: Ontology-based Knowledge Representation On Web Services and mentioning

confidence: 99%

See 4 more Smart Citations

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Fang

Liu

Romdhani

et al. 2016

Future Generation Computer Systems

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“…4 demonstrate the extensions AoFeCSO achieved in contrast to other existing models (i.e. [8,9,10,11,12,31]). …”

Section: Agility-centric Designmentioning

confidence: 81%

Section: In-depth Cloud Service Object Property Assertionmentioning

confidence: 99%

Section: Explicit Cloud Service and Concept Relationship Assertionmentioning

confidence: 99%

Section: Suitability For Service Retrieval and Recommendation Tasksmentioning

confidence: 99%

Section: Ontology-based Knowledge Representation On Web Services and mentioning

confidence: 99%

See 3 more Smart Citations

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Fang

Liu

Romdhani

et al. 2016

Future Generation Computer Systems

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Enhanced semantic similarity measure based on two‐level retrieval model

Djemaa

Nabli

Amous

2019

Concurrency and Computation

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Summary With the rapid spread of services in the Cloud computing environment, it is difficult for users to find the right service. Therefore, the necessity of a search engine with semantic focused crawler becomes a fundamental requirement. However, the huge size and varied functionalities of Cloud services on the Web, together with the lack of standardized and coherent description of services available, have a great effect for crawlers in order to provide effective Cloud services. To solve these issues, we propose a Cloud service discovery crawler that employs a two‐level semantic similarity measure based on both TF‐IDF and LDA models. Moreover, in order to automatically discover and categorize Cloud services, we present a Cloud Service Ontology (CSOnt) that contains a set of concepts defining Cloud service categories. Experimental results show that the proposed method enhances the performance of the focused crawlers and presents an efficient way to parse the Web and collect Web pages relevant to Cloud services.

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FIPA‐based reference architecture for efficient discovery and selection of appropriate cloud service using cloud ontology

Abbas

Mehmood

Lloret

et al. 2020

Int J Communication

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Cloud Computing (CC) is considered the latest emerging computing paradigm and has brought revolutionary changes in computing technology. With the advancement in this field, the number of cloud users and service providers is increasing continuously with more diversified services. Consequently, the selection of appropriate cloud service has become a difficult task for a new cloud customer. In case of inappropriate selection of a cloud services, a cloud customer may face the vendor locked-in issue and data portability interoperability problems. These are the major obstacles in the adoption of cloud services. To avoid these complexities, a cloud customer needs to select an appropriate cloud service at the initial stage of the migration to the cloud. Many researches have been proposed to overcome the issues but problems still exist in intercommunication standards among clouds and vendor locked-in issues. This research proposed an IEEE multi-agent FIPA (Foundation for Intelligent Physical Agent) compliance multi-agent reference architecture for cloud discovery and selection using cloud ontology. The proposed approach will mitigate the prevailing vendor locked-in issue and also alleviate the portability and interoperability problems in Cloud Computing. To evaluate the proposed reference architecture and compare it with the state-of-the-art existing approaches, several experiments have been performed by utilizing the commonly used performance measures. Analysis indicates that the proposed approach enables significant improvements in cloud service discovery and selection in terms of search efficiency, execution and response time.

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A Cloud Repository and Discovery Framework Based on a Unified Business and Cloud Service Ontology

Cited by 43 publications

References 13 publications

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Enhanced semantic similarity measure based on two‐level retrieval model

FIPA‐based reference architecture for efficient discovery and selection of appropriate cloud service using cloud ontology

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