Document Type



This item is available under a Creative Commons License for non-commercial use only


Computer Sciences

Publication Details

Successfully submitted in in partial fulfilment of the requirements for the degree of M.Sc. in Computing (Information Technology) to the Technological University Dublin, 2010


The advent of cloud computing in recent years has sparked an interest from different organisations, institutions and users to take advantage of web applications. This is a result of the new economic model for the Information Technology (IT) department that cloud computing promises. The model promises a shift from an organisation required to invest heavily for limited IT resources that are internally managed, to a model where the organisation can buy or rent resources that are managed by a cloud provider, and pay per use. Cloud computing also promises scalability of resources and on-demand availability of resources.

Although, the adoption of cloud computing promises various benefits to an organisation, a successful adoption of cloud computing in an organisation requires an understanding of different dynamics and expertise in diverse domains. Currently, there are inadequate guidelines for adopting cloud computing and building trust. Therefore, this research project aims at developing a roadmap called ROCCA (Roadmap for Cloud Computing Adoption), which provides organisations with a number of steps for adopting cloud computing and building trust. An associated framework called ROCCA Achievement Framework (RAF) is also proposed. RAF is a framework that uses the criteria in the ROCCA to build a framework for measuring the adherence level to the proposed roadmap.

This dissertation focuses on a range of strategic issues from a broad cross section of areas of expertise required to ensure a successful cloud computing adoption. It presents in detail the technological factors key to a successful cloud computing adoption, and it introduces the technology underlying cloud computing, and describes different cloud computing delivery and deployment models.