Table of Contents
Advances in Software Engineering
Volume 2012, Article ID 212343, 19 pages
Research Article

An SOA-Based Model for the Integrated Provisioning of Cloud and Grid Resources

1Dipartimento di Fisica, Università degli Studi di Cagliari, Complesso Universitario di Monserrato, 09042 Monserrato, Italy
2Istituto Nazionale di Fisica Nucleare (INFN), Complesso Universitario di Monserrato, Sezione di Cagliari, 09042 Monserrato, Italy

Received 15 June 2012; Revised 10 September 2012; Accepted 25 September 2012

Academic Editor: Guoquan Wu

Copyright © 2012 Andrea Bosin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In the last years, the availability and models of use of networked computing resources within reach of e-Science are rapidly changing and see the coexistence of many disparate paradigms: high-performance computing, grid, and recently cloud. Unfortunately, none of these paradigms is recognized as the ultimate solution, and a convergence of them all should be pursued. At the same time, recent works have proposed a number of models and tools to address the growing needs and expectations in the field of e-Science. In particular, they have shown the advantages and the feasibility of modeling e-Science environments and infrastructures according to the service-oriented architecture. In this paper, we suggest a model to promote the convergence and the integration of the different computing paradigms and infrastructures for the dynamic on-demand provisioning of resources from multiple providers as a cohesive aggregate, leveraging the service-oriented architecture. In addition, we propose a design aimed at endorsing a flexible, modular, workflow-based computing model for e-Science. The model is supplemented by a working prototype implementation together with a case study in the applicative domain of bioinformatics, which is used to validate the presented approach and to carry out some performance and scalability measurements.