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Along with the efforts to cope with the increase of functions which require higher communication bandwidth in vehicle networks using CAN-FD and vehicle Ethernet protocols, we have to deal with the problems of both the increased busload and more stringent response time requirement issues based on the current CAN systems. The widely used CAN busload limit guideline in the early design stage of vehicle network development is primarily intended for further frame extensions. However, when we cannot avoid exceeding the current busload design limit, we need to analyze in more detail the maximum frame response times and message delays, and we need good estimation and measurement techniques. There exist two methods for estimating the response time at the design phase, a mathematical worst-case analysis that provides upper bounds, and a probability based distributed response time simulation.

Multi-core systems are promising a cost-effective solution for (1) advanced vehicle features requiring dramatically more software and hence an order of magnitude more processing power, (2) redundancy and mixed-IP, mixed-ASIL isolation required for ISO 26262 functional safety, and (3) integration of previously separate ECUs and evolving embedded software business models requiring separation of different software parts. In this context, designing, optimizing and verifying the mapping and scheduling of software functions onto multiple processing cores becomes key. This paper describes several multi-core task design and scheduling design options, including function-to-task mapping, task-to-core allocation (both static and dynamic), and associated scheduling policies such as rate-monotonic, criticality-aware priority assignment, period transformation, hierarchical partition scheduling, and dynamic global scheduling.

Automotive HW/SW architectures are becoming increasingly complex to support the deployment of new safety, comfort, and energy-efficiency features. Such architectures include several software tasks (100+), messages (1000+), computational and communication resources (70+ CPUs, 10+ buses), and (smart) sensors and actuators (20+). To cope with the increasing system complexity at lowest development and product costs, highest safety, and fastest time to market, model-based rapid-prototyping development processes are essential. The processes, coupled with optimization steps aimed at reducing the number of software and hardware resources while satisfying the safety requirements, enable reduction of the system complexity and ease downstream testing/validation efforts. This paper describes a novel model-based design exploration and optimization process for the deployment of a set of software tasks on a dual-processor control module implementing a fail-safe strategy.

Today, gated networks with several buses are becoming standard in automotive E/E-systems but are evolving differently among the various vehicle manufactures, with different topologies, combinations of bus protocols, and speeds. Making the right architecture decisions requires systematic evaluation of the many alternatives during early design stages. However, there are many trade-offs in terms of performance, cost, extensibility, etc.. In this context, scheduling analysis is a powerful tool. It clarifies performance, end-to-end timing, and dynamic behavior. This enables evaluation of networking alternatives, foresight of bottlenecks, and provides guidance in the design process. In the paper, the application of scheduling analysis in automotive network exploration and optimization will be demonstrated. Specific emphasize will be put on end-to-end timing, migration from CAN to FlexRay, black-box integration and early-stage assumptions, extensibility, and trade-offs.

When designing safety-critical automotive systems, verification of timing and performance are key, especially the verification of hard deadlines and other critical timing constraints. Test- or simulation-based approaches suffer from corner-case coverage problems and are becoming less reliable as systems grow in size and complexity. Time-triggered mechanisms (e.g. OSEKtime and FlexRay) were proposed as a way out by providing better timing prediction. However, for reasons of cost, flexibility and reactivity, future cars will mostly likely contain a mix of event-triggered (ET) and time-triggered (TT) components that are combined synchronously and/or asynchronously, thereby further complicating timing. Scheduling analysis has recently matured to allow reliable timing verification and systematic optimization for ET, TT, and mixed systems.

Systems and network integration is a major challenge, and systematic analysis of the complex dynamic timing effects becomes key to building reliable systems. Very often, however, systematic analysis techniques are (considered) too restrictive with respect to established design practice. In this paper we present lessons learned from real-world case studies, in which OEMs have used the new SymTA/S scheduling analysis technology to evaluate different network choices with minimum effort. Thanks to its flexibility and supplier independence, SymTA/S can be applied in non-ideal situations, where other, more restricted technologies are inherently limited. Finally, we put the technology into relation with ongoing standardization activities.