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Fipa-Basedreference Architecture for Efficient Discovery and Selection of Appropriatecloud Service Using Cloud Ontology

Thesis Info

Access Option

External Link

Author

Ghulam Abbas

Institute

Virtual University of Pakistan

Institute Type

Public

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Subject

Software Engineering

Language

English

Link

http://vspace.vu.edu.pk/detail.aspx?id=349

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676721029770

Similar


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 are increasing continuously with more diversified services. Consequently, the selection of appropriate Cloud services 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, data portability, and interoperability issues. To avoid these complexities, a Cloud customer needs to select a required Cloud service at the initial stage of the migration to the Cloud. Many researchers have proposed their approaches to overcome these issues; however, problems still exist in inter-communication standards among Clouds and vendor locked-in issues. This thesis contributed an IEEE-FIPA (Foundation for Intelligent Physical Agent) compliance multi-agent reference architecture for efficient discovery and selection of Cloud services 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. In order to assess the proposed reference architecture and compare with the state-of-the-art approaches, three different use cases are presented. In addition, a number of experiments have been performed and results are obtained in terms of Precision, Recall and F-measure. The obtained results reveal that our proposed approach performs better in Cloud discovery and selection service with respect to search efficiency, execution, and response time.
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