Abstract
The paper proposes a dependability model to evaluate the behavior of a CAN network in scenarios of transient faults which affect data communications. Fault occurrence is modeled by a Markov Modulated Poisson Process (MMPP) which is capable to describe the typical behavior of electromagnetic interferences (EMI) that occur in industrial environments. An accurate and efficient representation of the network behavior is achieved by adopting a set of assumptions that reduce the pessimism level and which are closer to the real operating conditions. The model is based on Stochastic Petri Nets, which are a high-level modeling formalism able to produce very compact and efficient models, supporting both analytical and simulation solutions. Dependability measures are established from the fulfillment of the real-time constraints (deadlines) defined on messages exchanged between network nodes. Analytical and simulation solutions are both investigated. A case study is proposed to asses both model performance and network dependability. Copyright © 2005 IFAC.

Abstract
Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements.

Abstract
Industrial control systems architectures have been evolving to the decentralization of control tasks. This evolution associated with the time-critical nature Of these tasks, increases the dependability requirements for one of their most critical components: the communication system. Therefore, this is an important aspect on the control system design which must be properly evaluated. In this paper the dependability of a PROFIBUS network is assessed. By using of a fault injection framework the network operation is disturbed with fault scenarios which are representative of industrial environments. From these experiments, the stability of the PROFIBUS logical ring is analyzed, the main outages causes are identified and their probabilities are obtained.

Abstract

Abstract
The paper presents a framework to evaluate dependability of PROFIBUS-DP networks. An hierarchical modeling approach is proposed, which considers both the effects of permanent and transient faults. Stochastic Petri Nets are used as the modelling technique to obtain dependability models with emphasis in the use of analytical/numerical methods to provide model's solutions. In scenarios where its difficult to apply this approach, compact simulation models are derived.

Abstract