Modeling legal and regulative requirements for ranking alternatives of cloud-based services

Abstract

The decision to adopt a new technology in an organization is a complex task because of several Non-Functional Requirements (NFR) e.g., availability, interoperability, and presence of several alternatives, e.g., service providers can offer multiple packages. To support such a decision and to select the best alternative a Trade-off based Adoption Methodology for Cloud-based Infrastructure and Services (TrAdeCIS), based on NFR for cloud-based services, was proposed. This methodology makes the decision based on multi-criteria decision algorithms, namely the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Analytic Network Process (ANP). However, in addition, the decision for adopting cloud-based services is also influenced by the presence of various legal and regulative constraints. Therefore, it is crucial to understand, identify, and model the effect of such constraints on the evaluation of NFR and available alternatives. This paper, therefore, uses the Goal-oriented Requirement Language (GRL) to model the effect of legal and regulative constraints on ranking available alternatives with respect to NFR. The paper also discusses the extensibility and applicability of this methodology to other domains that require evaluating the effect of legal and regulative constraints on the adoption decision. To illustrate this, decisions within the domain providing better voice and data quality on-board train is also discussed in this paper.