Cloud Service Selection And Ranking: A Comparative Analysis Based On Energy Efficiency Parameters (Journal of Pharmaceutical Negative Results, 2022)
Amidst the expanding online usage and escalating demand for public cloud services, cloud service providers (CSPs) are grappling with the challenge of meeting diverse consumer demands while maintaining optimal computing capabilities. A key concern revolves around migrating applications and data across multiple cloud platforms, where variations in CSPs' pricing strategies and service offerings can significantly impact computing efficiency. For instance, while some CSPs may offer lower storage costs but higher computation expenses, others might adopt the opposite pricing structure. In addressing these complexities and enhancing the quality of service (QoS) for cloud clients, this study introduces a fuzzy cloud selection model. This model is designed to optimize the cloud service selection process by integrating criteria such as Power Consumption, Resource Utilization, Virtualization Efficiency, and Load Balancing within an energy-efficient framework.