A model based on a stochastic petri net approach for dependability evaluation of controller area networks (CAN)

Abstract

The paper proposes a dependability model to evaluate the behavior of a CANnetwork in scenarios of transient faults which affect data communications. Fault occurrenceis modeled by a Markov Modulated Poisson Process (MMPP) which is capable todescribe the typical behavior of electromagnetic interferences (EMI) that occur in industrialenvironments. An accurate and efficient representation of the network behavior isachieved by adopting a set of assumptions that reduce the pessimism level and which arecloser to the real operating conditions. The model is based on Stochastic Petri Nets, whichare a high-level modeling formalism able to produce very compact and efficient models,supporting both analytical and simulation solutions. Dependability measures are establishedfrom the fulfillment of the real-time constraints (deadlines) defined on messagesexchanged between network nodes. Analytical and simulation solutions are both investigated.A case study is proposed to asses both model performance and network dependability.