Cloud, edge, and fog computing: Trends and case studies
Abstract
Duplicate record, see https://ink.library.smu.edu.sg/sis_research/6813/. As it is done today, an informal - solely based on experts’ intuition - evaluation of profitability of adopting cloud services is undependable and not scalable as there are many conflicting factors and constraints such evaluation should account for. The revenue from service tenants and the cost of implementing the service architecture are the leading service factors that drive profitability. Cloud service architectures also need to handle a growing number of tenants with increasingly diverse requirements which must be weighed against the capabilities and costs of various service architectures, particularly single- versus multi-tenanted models. We believe a conceptual model enumerating the many decisions and factors affecting profitability of various cloud service offering strategies, and explicating dependencies among those factors is the first step to set up a ground for systematic analysis of service profitability. Based on such a model, we can define methods and implement tools to aid service providers in evaluating and selecting service offering strategies. In this work, we present a model of cloud service profitability, as well as an example of a method and tool that our model facilitates.