|Bibliography||Strauch, Steve; Andrikopoulos, Vasilios; Karastoyanova, Dimka; Vukojevic-Haupt, Karolina: Migrating eScience Applications to the Cloud: Methodology and Evaluation. |
In: Terzo, Olivier (ed.); Mossucca, Lorenzo (ed.): Cloud Computing with E-science Applications.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
CRC Press/Taylor & Francis, July 2015.
Article in Book.
|CR-Schema||D.2.11 (Software Engineering Software Architectures)|
H.3.4 (Information Storage and Retrieval Systems and Software)
|Keywords||Data Migration; Decision Support; Database layer; Application Refactoring|
eScience is an active field of research striving to enable faster scientific discovery and ground-breaking research in different scientific domains by means of information technology. In recent years Cloud computing has gained significant acceptance in both the enterprise application management and scientific computing for its promise to reduce infrastructure costs and provide virtually unlimited computational power and data storage - requirements of particular importance for businesses, and of even greater importance to scientists and research organizations. While research in this field is very active in providing novel concepts, techniques and principles towards building Cloud-native applications, there is a significant effort to Cloud-enable existing applications in order to reuse existing systems and therefore investments. Typically, Cloud-enabling applications is related to the migration of whole systems or parts of them on a public or private Cloud environment.
In this work we present a vendor- and technology-independent methodology for migrating the database layer of applications, and refactoring the application architecture. The methodology is applicable to applications in different application domains and is agnostic to the types of data sources. It fulfils requirements also presented in this work, which we have identified in collaboration with software engineers and domain experts in several research projects. We use this methodology to migrate the database layer of a scientific workflow management system (SimTech SWfMS), which we developed in the scope of our research activities in the SimTech project. The migration of the SimTech SWfMS has been done using the Cloud Data Migration Support Tool - a proof of concept implementation of the methodology. Both the introduced methodology and the supporting tool have been evaluated and our findings are presented.
|Copyright||CRC Press/Taylor & Francis |
|Department(s)||University of Stuttgart, Institute of Architecture of Application Systems|
|Entry date||January 20, 2015|