Can functional characteristics usefully define the cloud computing landscape and is the current reference model correct?

Journal article

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models (IaaS, PaaS, SaaS), and a number of characteristics (five in the final published version, but 13 in previous unpublished drafts).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.

Authors: Caithness, N; Drescher, M; Wallom, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: SpringerOpen
• Journal: Journal of Cloud Computing : Advances, Systems and Applications
• Volume: 10
• Issue: 6
• Publication date: 2017-06-05
• Acceptance date: 2017-05-23
• DOI: 10.1186/s13677-017-0084-1
• ISSN: 2192-113X
• Language: English
• Keywords: NIST definition of cloud computing; cloud computing; cloud ecosystem