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The FlexRay protocol [4] is likely to be the de facto standard for automotive communication systems. Hence, there is a need to provide hard performance guarantees on properties like worst case response times of messages, their buffer requirements, end-to-end latency (for example, from sensor to actuator), etc., for FlexRay based systems. The paper [11] provides an analysis for finding worst case response times of the messages transmitted on the FlexRay bus, but the analysis is done using ILP formulation and is thus computationally expensive. The paper [5] models the FlexRay in the analytic framework of Real-Time Calculus [12,3] and is compositional as well as scalable. In this paper, we show that the analysis of [5] may lead to results that are over optimistic; in particular, we show that obtaining the "upper service curves" is not trivial and does not follow the reasoning of the "lower service curves" which the authors obtain. We also provide tighter "lower service curves" than that of [5]. Finally we show that our model allows the messages to be of variable size which is not the case with [5].

Modern real-time embedded systems are highly heterogeneous and distributed. As a result, compositional methods play an important role in the design and analysis of such complex systems. One such compositional analysis method is based on Real-Time Calculus [4,14]. In this paper, we present an analysis of fixed priority non-preemptive scheduling with the Real-Time Calculus. Although fixed priority non-preemptive scheduling was modeled with the Real-Time Calculus previously [7], we show that the model gives overly pessimistic results. We also compare our analysis with the existing holistic scheduling analysis [10,3] through an example of a system using a Controller Area Network (CAN) bus [5]. The proposed method can be automated by incorporating it in the RTC Toolbox [13].

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