Prioritizing Cloud Services Using Quality Function Deployment: A QoS-Centric Decision Framework

The proliferation of cloud service providers offering diverse Quality of Service (QoS) attributes has made the selection of optimal services a complex multi-criteria decision-making problem. Traditional approaches such as the Analytic Hierarchy Process (AHP) and utility-based models, though systematic, often lack transparency in linking user-defined requirements to technical service attributes. This paper presents a generalized framework for cloud service selection based on Quality Function Deployment (QFD), enabling an intuitive and structured translation of customer QoS requirements into technical evaluation criteria. The proposed model constructs a House of Quality (HoQ) to map key customer-centric attributes, such as performance, cost, availability, reliability, and security, to measurable technical metrics, including response time, throughput, scalability, and SLA violations. By assigning relational weights and computing technical priority scores, the framework facilitates the ranking of cloud service alternatives. A realistic case study involving multiple IaaS providers demonstrates the applicability and effectiveness of the QFD model. Comparative analysis against AHP-based rankings highlights the interpretability and user-aligned prioritization benefits of QFD. This work contributes to a reusable decision support methodology for QoS awareness.