Name
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. cost benefit 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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SERVICES.2013.73 | SERVICES |
Keywords | Field | DocType |
evaluation experiences,cloud services evaluation,generic cloud evaluation experiment methodology,design of experiments (doe),generic cloud evaluation experiment,knowledge based systems,knowledge base,google appengine python runtime,cloud service,practical methodology,cloud computing domain,evaluation methodology,candidate cloud service,ceem,cloud evaluator,doe,sound methodology,convincing experimental result,design of experiments,suitable methodology,cloud computing,search engines | Services computing,Data mining,Computer science,Knowledge-based systems,Implementation,Cost–benefit analysis,Knowledge base,Python (programming language),Database,Benchmark (computing),Cloud computing | Conference |
ISBN | Citations | PageRank |
978-0-7695-5024-4 | 6 | 0.49 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zheng Li | 1 | 6 | 0.49 |
| Liam O'Brien | 2 | 367 | 30.01 |
| He Zhang | 3 | 817 | 65.63 |