Cloud computing is nowadays becoming a popular paradigm for the provision of computing infrastructure that enables organizations to achieve financial savings. On the other hand, there are some known obstacles, among which vendor lock-in stands out. Furthermore, due to missing standards and heterogeneities of cloud storage systems, the migration of data to alternative cloud providers is expensive and time-consuming. We propose an approach based on Semantic Web services and AI planning to tackle cloud vendor data lock-in problem. To complete the mentioned task, data structures and data type mapping rules between different types of cloud storage systems are defined. The migration of data among different providers of platform as a service is presented in order to prove the practical applicability of the proposed approach. Additionally, this concept was also applied to software as a service model of cloud computing to perform one-shot data migration from Zoho CRM to Salesforce CRM.
Publié le : 2018-11-21
Classification:
Parallel and Distributed Computing,
Cloud data portability, data migration, platform as a service, software as a service, data type mappings, semantic web services,
68-P20
@article{cai2018_5_1231,
author = {Darko Andro\v cec; Faculty of Organization and Informatics, University of Zagreb, Vara\v zdin and Neven Vr\v cek; Faculty of Organization and Informatics, University of Zagreb, Vara\v zdin},
title = {Ontology-Based Resolution of Cloud Data Lock-in Problem},
journal = {Computing and Informatics},
volume = {36},
number = {6},
year = {2018},
language = {en},
url = {http://dml.mathdoc.fr/item/cai2018_5_1231}
}
Darko Andročec; Faculty of Organization and Informatics, University of Zagreb, Varaždin; Neven Vrček; Faculty of Organization and Informatics, University of Zagreb, Varaždin. Ontology-Based Resolution of Cloud Data Lock-in Problem. Computing and Informatics, Tome 36 (2018) no. 6, . http://gdmltest.u-ga.fr/item/cai2018_5_1231/