A Taxonomy and Survey of Cloud Computing Systems

TLDR

The computational world is increasingly large and complex, and cloud computing has emerged as a popular model for processing massive data volumes on commodity clusters, yet a concrete definition remains elusive. The study develops a comprehensive taxonomy of cloud computing architecture and uses it to identify similarities, differences, and research gaps among existing services. The authors apply the taxonomy to survey existing cloud computing services from projects such as Google, Force.com, and Amazon. The survey reveals architectural similarities and differences among services and highlights areas needing further research.

Abstract

The computational world is becoming very large and complex. Cloud Computing has emerged as a popular computing model to support processing large volumetric data using clusters of commodity computers. According to J.Dean and S. Ghemawat [1], Google currently processes over 20 terabytes of raw Web data. It's some fascinating, large-scale processing of data that makes your head spin and appreciate the years of distributed computing fine-tuning applied to today's large problems. The evolution of cloud computing can handle such massive data as per on demand service. Nowadays the computational world is opting for pay-for-use models and Hype and discussion aside, there remains no concrete definition of cloud computing. In this paper, we first develop a comprehensive taxonomy for describing cloud computing architecture. Then we use this taxonomy to survey several existing cloud computing services developed by various projects world-wide such as Google, force.com, Amazon. We use the taxonomy and survey results not only to identify similarities and differences of the architectural approaches of cloud computing, but also to identify areas requiring further research.