Stefan Kuntz

Enabling Scheduling Analysis for AUTOSAR Systems

AUTOSAR (Automotive Open System Architecture) is enjoying increasing interest and broad acceptance in the automotive domain. AUTOSAR aims at defining an open standardized software architecture to face future challenges in automotive development including the development of time-critical systems (e.g. brake-by-wire or steer-by-wire). Mastering the development of such systems requires being able to analyze their real-time behavior. Scheduling analysis is the theory that studies how far a real-time system may satisfy its real-time requirements against its real-time properties. In this paper, we will study to what extent it is possible to apply some of those scheduling analysis techniques on real-time systems deployed on AUTOSAR-compliant architectures. The paper focuses on scheduling analysis techniques implemented in one open source tool. A concrete case study shows the feasibility of the approach and shows scheduling analysis results.

On the gap between schedulability tests and an automotive task model

Abstract In this paper, we study the adequacy of available schedulability tests for monoprocessor fixed-priority systems to enable performing scheduling analysis for automotive applications. We show that, in spite of the work carried out during the last decade to enhance these tests in order to support more realistic task model, a gap still exists between the task model considered in these tests and the usual automotive task model. However, we claim that an extension of these tests is possible to support some of the uncovered automotive features. The aim of this study is to raise discussion and make researchers involved in the development of such schedulability tests be aware of the effort needed to bridge the gap between current schedulability tests and automotive task model mostly used. The study is illustrated by showing the concrete challenges faced when applying scheduling analysis to a case study derived from a real engine control application.

Analysis and validation of AUTOSAR models

As the rise of single-core processing power is exhausted due to technical limitations, the automotive branch is forced to migrate its control unit software to architectures that feature multiple Independent Execution Units (IEUs). This policy shift brings along new problems resulting from the tremendously increased complexity of such systems. Facing these challenges, software engineers have to cope with possible data inconsistencies caused by, e.g., race conditions or cycles. Being an important and standardized software architecture for electronic control units, the Automotive Open System Architecture (AUTOSAR) provides the basis for tools that support the complexity handling when migrating to architectures with multiple IEUs. Our concept is realized by a tool that executes data dependency analyses directly on AUTOSAR models, determines critical dependencies, automatically solves trivial problems and provides semi-automatic resolution of advanced conflicts. To support the actual parallelization of the system, the tool additionally determines groups of executable units that are suitable to run on a common IEU. This appreciably facilitates the validation of AUTOSAR models and the search for a good mapping of the processing tasks to IEUs.

Timing modeling with AUTOSAR: current state and future directions

In the automotive industry, the Automotive Open System Architecture AUTOSAR is established as a de-facto standard and is applied in a steadily increasing number of development projects. In addition, AUTOSAR attracted the attention of other non-automotive industries, like railway, agriculture and construction machines, power generation and marine technology. The first versions of the standard successfully achieved the objective of integrating in a common framework various components from different suppliers and ensuring their interfaces interoperability. In actual and future versions of the standard, the objective becomes even more ambitious as it considers behavioral and timing characteristics of these components. Therefore, this paper presents the current status of AUTOSAR Release 4.0 concerning the behavioral modeling and timing characterization of components and opens several research and development directions for future extensions of the standard.

AUTOSAR vs. MARTE for enabling timing analysis of automotive applications

Automotive software systems are characterized by increasing complexity and tight requirements on safety and timing. Recent industrial experience has indicated that model-based and component-based approaches can help improve the overall system quality, foster reuse and evolution, and increase the potential for automatic validation and verification. In this paper, we discuss some crucial specification capabilities that need to be satisfied by modeling languages to enable scheduling analysis aware modeling for automotive applications. We evaluate the extent to which two major industry-based languages, MARTE and AUTOSAR, satisfy those needs.

Parallelizing highly complex engine management systems: EMS Parallelization

The automotive industry seeks to include more and more features in its vehicles. For this purpose, the necessary policy shift towards multi‐core technology is in full swing. To eventually exploit the extra processing power, there is much additional effort needed for coping with the tremendously increased complexity. This is largely due to the elaborate parallelization process that spans a vast search space. Consequently, there is a strong need for innovative methods and appropriate tools for the migration of legacy single‐core software. We use the results of a data dependency analysis performed on AUTOSAR system descriptions to determine advantageous partitions as well as initial task‐to‐core mappings. Afterwards, the extracted information serves as input for the simulation within a multi‐core timing tool suite. Here, the initial solution is evaluated with respect to proper scheduling and metrics like cross‐core communication rates, communication latencies, or core load distribution. A subsequent optimization process improves the initial solution and enables a comparative assessment. To demonstrate the benefit, we substantially expand a previous case study by applying our approach to two complex engine management systems and by showing the advantages compared to a parallelization process without preceding dependency analysis and initial partition/mapping suggestions.

Verification of behavioral compatibility in the Virtual Integration methodology

The advantages of component-based systems include reuse of generic components as well as adaption through variants. However, they bare a high risk of containing incompatibilities between components, due to the lack of control over the integration-relevant aspects of their components. Current development processes are able to detect incompatibilities between components only at very late stages of system development. The Virtual Integration methodology is an approach to detect and to solve compatibility issues during early stages of system design. The methodology supports developers with a set of measures to reduce the risk of incompatibilities to a minimum at each abstraction layer of their system architecture. Realtime requirements of embedded systems make it necessary to support the methodology with a formal model, which can describe dynamic properties of these systems. In our approach, we use interface automata because they offer a lightweight formalism to describe the behavior of components and to verify their compatibility based on these descriptions. In a feasibility study we show, to which extend interface automata are adequate for the foresaid purpose in the automotive application field.