A Cloud Service Selection Model Based on User-Specified Quality of Service Level

摘要

Recently, it emerges lots of cloud services in the cloud service market. After many candidateservices are initially chosen by satisfying both the behavior and functional criteria of a targetcloud service. Service consumers need a selection model to further evaluate nonfunctional QOSproperties of the candidate services. Some prior works have focused on objective andquantitative benchmark-testing of QOS by some tools or trusted third-party brokers, as well asreputation from customers. Service levels have been offered and designated by cloud serviceproviders in their Service Level Agreement (SLA). Conversely, in order to meet userrequirement, it is important for users to discover their own optimal parameter portfolio forservice level. However, some prior works focus only on specific kinds of cloud services, orrequire users to involve in some evaluating process. In general, the prior works cannot evaluatethe nonfunctional properties and select the optimal service which satisfies both user-specifiedservice level and goals most either. Therefore, the aim of this study is to propose a cloud serviceselection model, CloudEval, to evaluate the nonfunctional properties and select the optimalservice which satisfies both user-specified service level and goals most. CloudEval applies awell-known multi-attribute decision making technique, Grey Relational Analysis, to theselection process. Finally, we conduct some experiments. The experimental results show thatCloudEval is effective, especially while the quantity of the candidate cloud services is muchlarger than human raters can handle.