Design and modeling of CT systems with GSPN

Abstract

To accurately model the complex behavior of computed tomography (CT) systems, generalized stochastic Petri nets (GSPNs) are used. This approach makes it possible to examine the concurrence and synchronization characteristics, as well as the reliability and performance of the system. To overcome the difficulties of the state space explosion associated with GSPN, an approximate superposition technique is presented. Utilizing the flexibility of the GSPN technique, the model is able to consider not only the failure of each individual processor, but also the complicated failure recovery schemes and communication protocols among processors.<>