Abstract
The NIST definition of cloud computing has been accepted by the majority of the community as the best available description to fully capture the variety of factors which determine how different stakeholders create, use or interact with cloud computing. With the breadth of the cloud computing landscape there is a need being expressed from within different cloud activities to consider how it may be best segmented so that the diversity might be more easily understood by the different stakeholders. The NIST definition considers four different deployment models (Private, Public, Hybrid, Community Cloud), three different service models (IaaS, PaaS, SaaS), and a number of characteristics (five in the final published version, but 13 in previous unpublished drafts). Exploring the definition further, this study aims to answer two questions: first, how can we use the affinity that different activities have with the definition’s characteristics and second, how well does the definition describe the whole cloud ecosystem? We find that utilising a quantitative methodology shows a clustering of different cloud projects and activities that are technically aligned and therefore likely to benefit from interactions and shared learning, and that the final (short-list) definition is more robust than the draft (long-list) definition. Finally, we present a segmentation of the cloud landscape that we believe can best support a sharing of learning between projects in individual clusters.
Highlights
Since the emergence of cloud computing as a distinct paradigm within distributed computing, and as an important emerging market for ICT based services, there have been a number of efforts to support and encourage the adoption of cloud computing, as well as to foster a more geographically diverse cloud computing provider community
We describe this reference model more fully below but here we highlight a key feature—the model defines a limited set of functional characteristics that can be used to derive a quantitative description of the emerging cloud computing landscape
The aims of this study were to characterise the abstract landscape of cloud computing, determine if that characterization is robust, and to learn something from the landscape to the benefit cloud participants and stakeholders
Summary
Since the emergence of cloud computing as a distinct paradigm within distributed computing, and as an important emerging market for ICT based services, there have been a number of efforts to support and encourage the adoption of cloud computing, as well as to foster a more geographically diverse cloud computing provider community This has resulted in a large number of research and innovation projects receiving European Commission (EC) support over the past five years through the FP7 and. UK enough to share learning on both technical and social best practices would naturally emerge This has resulted in only limited appeal, as it has been unclear to participants exactly how the clusters are to be useful or effective as they are only superficially similar but differ widely in the cloud technologies and techniques in use. We describe this reference model more fully below but here we highlight a key feature—the model defines a limited set of functional characteristics that can be used to derive a quantitative description of the emerging cloud computing landscape
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