Performance Modeling of Client-Server with Wibree Application Using Queueing Petri Nets and Markov Algorithm

This paper focuses on how the Petri net models can be exploited by Markov algorithm for performance modelling of client server using Wibree applications. We study a real world application and demonstrate the benefits in terms of modeling power and expressiveness that Wibree technology and QPN models with Markov algorithm provide over conventional modeling paradigms such as queueing networks and Petri nets. QPNs facilitate the integration of both hardware and software aspects of the system behavior in the improved model. This lends itself very well to modeling distributed component-based systems, such as modern e-business applications. Currently available tools and techniques for QPN analysis suffer the state space explosion problem, imposing a limit on the size of the models that are tractable. In addition to Wibree technology in the systems and using QPNs one can easily model simultaneous resource possession synchronization, blocking and contentions for software resources. QPNs are very powerful as a performance analysis and prediction tool. Improved solution methods, which enables larger models to be analyzed and they need to be developed. By demonstrating the power of QPNs as a modeling paradigm in realistic scenarios. We hope to motivate further research in this area.