Int. J. of Big Data Intelligence   »   2014 Vol.1, No.3

 

 

Title: Migrating enterprise applications to the cloud: methodology and evaluation

 

Authors: Steve Strauch; Vasilios Andrikopoulos; Dimka Karastoyanova; Frank Leymann; Nikolay Nachev; Albrecht Stäbler

 

Addresses:
Institute of Architecture of Application Systems, University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany
Institute of Architecture of Application Systems, University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany
Institute of Architecture of Application Systems, University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany
Institute of Architecture of Application Systems, University of Stuttgart, Universitaetsstrasse 38, 70569 Stuttgart, Germany
NovaTec Holding GmbH Dieselstrasse 18/1 70771 Leinfelden-Echterdingen, Germany
NovaTec Holding GmbH, Dieselstrasse 18/1, 70771 Leinfelden-Echterdingen, Germany

 

Abstract: Migrating existing on-premise applications to the cloud is a complex and multi-dimensional task and may require adapting the applications themselves significantly. For example, when considering the migration of the database layer of an application, which provides data persistence and manipulation capabilities, it is necessary to address aspects like differences in the granularity of interactions and data confidentiality, and to enable the interaction of the application with remote data sources. In this work, we present a methodology for application migration to the cloud that takes these aspects into account. In addition, we also introduce a tool for decision support, application refactoring and data migration that assists application developers in realising this methodology. We evaluate the proposed methodology and enabling tool using a case study in collaboration with an IT enterprise.

 

Keywords: data migration; application migration; decision support; database layer; application refactoring; cloud computing; interaction granularity; data confidentiality; remote data sources.

 

DOI: 10.1504/IJBDI.2014.066319

 

Int. J. of Big Data Intelligence, 2014 Vol.1, No.3, pp.127 - 140

 

Available online: 16 Dec 2014

 

 

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