B. Rimal, E. Choi, and I. Lumb. Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC, page 44--51. Washington, DC, USA, IEEE Computer Society, (2009)
DOI: 10.1109/NCM.2009.218
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.
%0 Conference Paper
%1 Rimal:2009:TSC:1683301.1684085
%A Rimal, Bhaskar Prasad
%A Choi, Eunmi
%A Lumb, Ian
%B Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
%C Washington, DC, USA
%D 2009
%I IEEE Computer Society
%K cloud computing im informationsmanagement
%P 44--51
%R 10.1109/NCM.2009.218
%T A Taxonomy and Survey of Cloud Computing Systems
%U http://virtualcluster.googlecode.com/files/A%20Taxonomy%20and%20Survey%20of%20Cloud%20Computing%20System.pdf
%X 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.
%@ 978-0-7695-3769-6
@inproceedings{Rimal:2009:TSC:1683301.1684085,
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.},
acmid = {1684085},
added-at = {2012-05-30T18:52:08.000+0200},
address = {Washington, DC, USA},
author = {Rimal, Bhaskar Prasad and Choi, Eunmi and Lumb, Ian},
biburl = {https://www.bibsonomy.org/bibtex/2b9508abb7fb296b73b1449059b397679/griesbau},
booktitle = {Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC},
description = {A Taxonomy and Survey of Cloud Computing Systems},
doi = {10.1109/NCM.2009.218},
interhash = {c75c1617dff84e0745fd7587af4f3081},
intrahash = {b9508abb7fb296b73b1449059b397679},
isbn = {978-0-7695-3769-6},
keywords = {cloud computing im informationsmanagement},
numpages = {8},
pages = {44--51},
publisher = {IEEE Computer Society},
series = {NCM '09},
timestamp = {2012-05-30T18:52:08.000+0200},
title = {A Taxonomy and Survey of Cloud Computing Systems},
url = {http://virtualcluster.googlecode.com/files/A%20Taxonomy%20and%20Survey%20of%20Cloud%20Computing%20System.pdf},
year = 2009
}