CEEM: A Practical Methodology for Cloud Services Evaluation

Conference paper


Li, Zheng, O'Brien, Liam and Zhang, He 2013. CEEM: A Practical Methodology for Cloud Services Evaluation. 2013 IEEE Ninth World Congress on Services. IEEE. pp. 44-51
AuthorsLi, Zheng, O'Brien, Liam and Zhang, He
TypeConference paper
Abstract

Abstract—Given an increasing number of Cloud services
available in the market, evaluating candidate Cloud services
is crucial and beneficial for both service customers (e.g. costbenefit analysis) and providers (e.g. direction of improvement).
When it comes to performing any evaluation, a suitable
methodology is inevitably required to direct experimental
implementations. Nevertheless, there is still a lack of a sound methodology to guide the evaluation of Cloud services. By borrowing the lessons from evaluation of traditional computing systems, referring to the guidelines for Design of Experiments (DOE), and summarizing the existing experiences of real experimental studies, we proposed a generic Cloud Evaluation Experiment Methodology (CEEM) for Cloud services evaluation.
Furthermore, we have established a pre-experimental
knowledge base and specified corresponding suggestions to
make this methodology more practical in the Cloud Computing
domain. Through evaluating the Google AppEngine Python
runtime as a preliminary validation, we show that Cloud
evaluators may achieve more rational and convincing experimental results and conclusions following such an evaluation methodology.

Year2013
Conference2013 IEEE Ninth World Congress on Services
PublisherIEEE
Accepted author manuscript
License
CC BY-ND
Publication dates
Print2013
Publication process dates
Deposited11 Dec 2013
Book title2013 IEEE Ninth World Congress on Services
Web address (URL)http://dx.doi.org/10.1109/SERVICES.2013.73
Page range44-51
Permalink -

https://repository.uel.ac.uk/item/85y0z

Download files


Accepted author manuscript
06655674.pdf
License: CC BY-ND

  • 95
    total views
  • 301
    total downloads
  • 0
    views this month
  • 5
    downloads this month

Export as