Performance evaluation of cloud e-marketplaces using non preemptive queuing model

With the drift of consumers to the Cloud e-marketplaces looking for affordable and cost effective services, waiting time is of interest to every consumer and also a key source of competitive advantage for any cloud e-market provider. Keeping consumers' waiting may incur high costs of consumer's dissatisfaction, such as loss of future business and actual processing costs of complaints. The evaluation of performance impact on consumers' waiting time has not been fully addressed in the context of differentiated service provisioning. In this research, we conducted a modelling and evaluation of a typical cloud e-marketplace using two classes of consumers under non preemptive priority discipline. We studied and compared the performance impact of these two classes in regard to the non-priority discipline. Our approach used the analytical and simulation model. Early results revealed that the average total waiting time is independent of the service discipline. Furthermore, unlike the Non-Priority where the service distribution of the two classes are almost equal when the server utilization increases, the class 1 consumers' waiting time approaches finite limit and that of class 2 consumers deviated slightly from the average total waiting time under the Non preemptive Priority.