An Approach to Composite QoS Parameter based Web Service Selection

In any enterprise application Quality of Service (QoS) is an important attribute for selecting a service during the service composition process. Although availability and reliability have been considered as the predominant factors for estimating reputation, two aspects are lacking in the literature. First, their use is limited to composite service level and does not count at the atomic level. Second, their combined effect is not evaluated. Hence, the methodology of estimating reputation and its use for atomic service will have compounding effect on the overall quality of the composite service. We feel, better estimation of QoS can be done with both factors considered together on the simple premise that availability tells about only the probability of that service being up/running, but doesnot tell about its failure trend. In our work we present mathematical modelling of these predominant QoS factors using Markov model and Weibull analysis. A scenario has been simulated using Colored Petri Nets (CPN) to study the behavioral aspects. The outcome of our research is two fold. First, counting on probability of a service being up/running and its failure trend, together, results in a better estimation of its behavior and helps selecting the most appropriate one. Second, this resulted in selection of a service with higher reputation but lower usage cost, as opposed to using a single factor that resulted in higher reputation with higher cost