A decision framework for cloud migration: A hybrid approach. Issue 6 (29th September 2022)

• Record Type: Journal Article
• Authors: Hosseini Shirvani, Mirsaeid; Amin, Gholam R.; Babaeikiadehi, Sara
• Is Part Of: IET software. Volume 16:Issue 6(2022)
• Page Start: 603
• Page End: 629
• Publication Date: 2022-09-29
• Subjects: analytic hierarchy process -- cloud computing -- cloud decision model -- Delphi method -- Net Present Value -- requirement engineering; Computer software -- Periodicals; Software engineering -- Periodicals; 005.1
• DOI: 10.1049/sfw2.12072
• Languages: English
• ISSNs: 1751-8806

Abstract

Abstract: Cloud computing is utilised for information technology outsourcing of either industries or organisations. There are several inhibitors and motivations related factors to determine whether one can embrace the cloud services or not. Therefore, this paper presents a holistic and flexible cloud decision framework by taking a wide spectrum weighted factors related to the acceptance or denial of the cloud services. To have sustainable decision and obviating the shortcomings of the existing approaches on the cloud service adoption, a deep understanding of organisation's business process requirements and cost implications is required. To utilise the proposed model, the functional and non‐functional requirements associated to the business process of an adopter organisation must be specified. To reach a concrete decision, a hybrid approach is applied by incorporating the analytic hierarchy process and Delphi methods to prevent subjective outcomes and to have diverse experiences at the same time. To support the decision model, some economic theories and Moore law are used. To verify the proposed model, a Telecommunication Company is considered as a case study for its 6‐year plan of investment. The simulation results of conducted scenarios for the mentioned mid‐scale case study prove that it is logical to establish on‐premises a private datacenter and utilising the hybrid deployment once it encounters abrupt burst of resource demand. Altogether, the proposed holistic model can be customised for different users with different scales.