Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33275
Title: Evaluating cloud platform architecture with the CARE framework
Authors: Zhao, L
Liu, A
Keung, J
Keywords: Amazon EC2
Amazon S3
Amazon SimpleDB
Amazon Web Services
CARE
Cloud computing
Google App Engine
Microsoft Azure
Performance Evaluation
Issue Date: 2010
Publisher: IEEE
Source: 2010 17th Asia Pacific Software Engineering Conference (APSEC), November 30 2010-December 3 2010, Sydney, NSW, p. 60-69 How to cite?
Abstract: There is an emergence of Cloud application platforms such as Microsoft's Azure, Google's App Engine and Amazon's EC2/SimpleDB/S3. Startups and Enterprise alike, lured by the promise of `infinite scalability', `ease of development', `low infrastructure setup cost' are increasingly using these Cloud service building blocks to develop and deploy their web based applications. However, the precise nature of these Cloud platforms and the resultant Cloud application runtime behavior is still largely an unknown. Given the black box nature of these platforms, and the novel programming and data models of Cloud, there is a dearth of tools and techniques for enabling the rigorously evaluation of Cloud platforms at runtime. This paper introduces the CARE (Cloud Architecture Runtime Evaluation) approach, a framework for evaluating Cloud application development and runtime platforms. CARE implements a unified interface with WSDL and REST in order to evaluate different Cloud platforms for Cloud application hosting servers and Cloud databases. With the unified interface, we are able to perform selective high stress and low stress evaluations corresponding to desired test scenarios. Result shows the effectiveness of CARE in the evaluation of Cloud variations in terms of scalability, availability and responsiveness, across both compute and storage capabilities. Thus placing CARE as an important tool in the path of Cloud computing research.
URI: http://hdl.handle.net/10397/33275
ISBN: 978-1-4244-8831-5
978-0-7695-4266-9 (E-ISBN)
ISSN: 1530-1362
DOI: 10.1109/APSEC.2010.17
Appears in Collections:Conference Paper

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