The use of cloud computing in various data-centric applications such as wireless sensor networks (WSN) has attracted a large number of users because the cloud integrates various features in the applications such as scalability, availability, security, etc. The adoption of on-demand services of the cloud has raised competition among various cloud service providers (CSPs).The various CSPs charge different subscription charges for their services, such as storage space and virtual processors. Hence, the selection of the most suitable cloud is a must. In this paper, a multi-criteria dual-membership-based fuzzy technique (MC-DMFT) is proposed to improve cloud users’ QoS experience and address the hurdle of choosing an appropriate cloud service. We have used the MC-DMFT method to define the phases of the overall process involved in the cloud service selection and calculated the rank values for different users for QoS. Existing approaches are not proficient enough, and they require a very complex computation process. The proposed approach uses the concept of fuzzy technique to rank various cloud service providers based on capacity, pricing, security, performance, and maintenance as key parameters. The comparative analysis shows the effectiveness and potential of the proposed method.