The fourth industrial revolution (Industry 4.0) anticipates unplanned changes of production processes. Production changes may trigger synthesis, and preferably optimization, of architecture-level decisions, such as service deployment and composition. Performing such architecture-level decisions manually is difficult due to the ever-rising complexity of Industry 4.0 systems. In order to (semi-)automate the architecture synthesis and optimization, we propose an approach of service deployment and composition by using existing domain models. Our contribution is threefold: (1) We suggest a workflow with domain models for architecture synthesis in the industrial automation. (2) We display the formalization on a part of the workflow and provide an initial prototype of service deployment synthesis using a satisfiability modulo theories (SMT) solver. (3) We envision a way of service composition and code generation, and prototypically implemented it as conclusion of the suggested workflow. We demonstrate the practical use of the proposed approach in the Industry 4.0 scenario, i.e., flexible production of new products.

Architectural design decisions, such as service deployment and composition, plant layout synthesis, or production planning, are an indispensable and overarching part of an industrial manufacturing system design. In the fourth industrial revolution (Industry 4.0), frequent production changes trigger their synthesis, and preferably optimization. Yet, knowledge on architecture synthesis and optimization has been scattered around other domains, such as generic software engineering. We take a step towards synthesizing current knowledge on architectural design decisions in Industry 4.0. We developed a taxonomy describing architectural models, design decisions, and optimization possibilities. The developed taxonomy serves as a guideline for comparing different possibilities (e.g., application of different optimization algorithms) and selecting appropriate ones for a given context. Furthermore, we reviewed and mapped 30 relevant research works to the taxonomy, identifying research trends and gaps. We discuss interesting, and yet uncovered topics that emerged from our review.

The desired flexibility of industrial automation systems foresees among others flexible deployment and execution of control applications on distributed control nodes. This task can be performed more efficiently by an automated deployment algorithm yielding a valid deployment and optimizing non-functional objectives.Although extensively investigated, automated deployment approaches for the automotive domain cannot be translated to industrial control applications, due to a different execution semantics. Thus, in this paper, we present a method of satisfiability modulo theories (SMT)-based automated deployment of the industrial automation systems. We formalize and implement domain-relevant constraints and objectives. Our contribution is threefold: 1) we formalize the functional coupling and end-to-end deadline constraints and objectives while considering the semantics of control applications, 2) we encode the deployment problem into an SMT form, and 3) we validate the approach on an abstract example and a domain-relevant use case.The results obtained in this paper will allow application engineers to fulfill functional and real-time requirements by automatically solving the deployment problem.

In order to cope with the rising complexity of today's systems, model-based development of software-intensive embedded systems has become a de-facto standard in recent years. In a previous work, we demonstrated how such a model-based approach can enable automatization of certain development steps, namely the deployment of logical (platform-independent) system models to technical (platform-specific) system models. Together with Continental, we especially focused on industrial applicability.

In order to cope with the rising complexity of today's systems, model-based development of software-intensive embedded systems has become a de-facto standard in recent years. Such a development approach enables a variety of frontloading methods. Design space exploration is one of those techniques. However, in order to properly perform a valid exploration, a system model has to have a certain quality. This requires dedicated, meaningful models as an input according to well-known design principles, which entails the structuring of models according to different viewpoints and usage of dedicated models for each of these viewpoints.In this work, we demonstrate how, based on an industrial application model represented in SysML, design space exploration methods can be efficiently applied to enable the synthesis of deployments from a logical (platform-independent) system models to technical (platform-specific) system models. Moreover, we will demonstrate the applicability of this approach by a project conducted with Continental.

The solution of many engineering and scientific problems requires the exploration of a huge n-dimensional design space. Typical approaches rely on an abstract problem model consisting of a system model (description of the problem's variable couplings) and an optimization specification defining the objectives as well as the constraints bounding the design space. Advances in solver technologies enabled to efficiently search the solution space, however the diversity of the approaches led to problem descriptions that are difficult to reuse, as well as to solutions that are hard to compare. Our Exploration Meta-Model (EMM) addresses this issue by providing a unified language for optimization specifications that is a well-defined basis for model-based implementations of solver-independent design-space exploration (DSE) tool-chains. The EMM is a light-weight framework that allows to a) describe optimization specifications independent of particular optimization methods and solvers, b) relate solutions and optimization specifications, and c) define domain profiles that provide high-level optimization specifications that ease the adoption of automated DSE by domain experts. The applicability of our framework to different optimization methods is demonstrated by applying it to the generic vector optimization problem and to single-objective linear programs. The EMM's support to relate optimization results to input specifications is exercised for the Opt4J framework. Finally, a profile for real-time embedded systems demonstrates how the EMM can be tailored to specific domains.

With a growing demand for complex, safety-critical features in automotive vehicles, functional safety is a key issues of automotive software development. Consequently, standards like ISO26262 propose methods and techniques for the systematic development of automotive software. Furthermore, the growing amount of functionality -- including active safety systems or automated driver assistance functions -- on the control of the vehicle dynamics and the correspondingly used more powerful electronic platforms requires methods supporting the development of systems in an increasingly complex design space. In this contribution, an approach is presented that supports the allocation of software functions to hardware elements in an automated fashion, respecting the separation constraints concerning assurances levels.

Fault-tolerant distributed embedded systems have to react properly on the occurrence of faults in order to avoid harm to the system or its environment. Faulty system resources have to be isolated from the remaining system. Hence, these resources become unavailable, leading to a decreasing number of available resources and input data. In such cases, mechanisms like graceful degradation may be applied to ensure that the system does not turn off completely, but degrades its provided set of functional features gracefully. It must be ensured that the remaining intact resources are efficiently used to execute at least those features, which are required to behave fail-operational. In this paper, we investigate deployments of mixed-critical software components to a fault-tolerant system platform. We introduce a formal model of software components and their publish/subscribe based communication channels. We use this model to analyze the graceful degradation of the system in different scenarios of failing execution hardware. This includes also the explicit deactivation of software components due to unavailable required input data. Our analysis is based on using an SMT solver and contributes to guarantee that all requirements with respect to fail-operationality are met by the system design. The approach is evaluated by an example and a scalability analysis.

Background: The mobility domains are moving towards the adoption of multicore technology. Appropriate methods, techniques, and tools need to be developed or adapted in order to fulfill the existing requirements. This is a case for design space exploration methods and tools. Objective: Our goal was to understand the importance of different design space exploration goals with respect to their relevance, frequency of use, and tool support required in the development of multicore systems from the point of view of the ARAMiS project members. Our aim was to use the results to guide further work in the project. Method: We conducted a survey regarding the current state of the art in design space exploration in industry and research and collected the expectations of project members regarding design space exploration goals. Results: The results show that design space exploration is an important topic in industry as well as in research. It is used very often with different important goals to optimize the system. Conclusions: Current tools provide only partial solutions for design space exploration. Our results can be used for improving them and guiding their development according to the priorities explained in this contribution.