Performance Evaluation of Self-reconfigurable Service-oriented Software With Stochastic Petri Nets

Open-world software is a paradigm which allows to develop distributed and heterogeneous software systems. They can be built by integrating already developed third-party services, which use to declare QoS values (e.g., related to performance). It is true that these QoS values are subject to some uncertainties. Consequently, the performance of the systems using these services may unexpectedly decrease. A challenge for this kind of software is to self-adapt its behavior as a response to changes in the availability or performance of the required services. In this paper, we develop an approach to model self-renconfigurable open-world software systems with stochastic Petri nets. Moreover, we develop strategies for a system to gain a new state where it can recover its availability or even improve its performance. Through an example, we apply these strategies and evaluate them to discover suitable reconfigurations for the system. Results will announce appropriate strategies for system performance enhancement.