Cyber-Physical Systems (CPSs) integrate computing, communication and control processes. Close interactions between the cyber and physical worlds occur in time and space frequently. Therefore, both temporal and spatial information should be taken into consideration when specifying properties of CPS systems for verification. However, how to formulate properties specifying spatial together with temporal features is still an unsolved problem in the CPS. In this paper, we propose an approach to analyze the spatio-temproal properties of CPS. A spatio-temporal logic is developed, including the syntax and semantics of the logic. With that logic, properties of both states, transitions and global systems could be specified, paving the way for further verification. To show the efficiency of the approach , a Train Control System is introduced as a case study. Meanwhile, more details about how to specifying properties of CPS systems with our method are elaborated.

No abstract

Bayesian networks have been used widely in modelling complex network systems. Probabilistic inferences are normal requirements in control and management of networks, particularly in modelling diagnosis systems for large and complex networks in probabilistic and dynamic environments. This paper provides a random simulation mechanism to construct the simulation in Bayesian networks for probabilistic inference, so that the simulation in Bayesian netviorks is close to real lilfe networks and further the intelligent decision in management of networks can be obtained.