Scientific publications

We present a three-step binding algorithm for applications in the form of directed acyclic graphs (DAGs) of tasks with deadlines, that need to be bound to a shared memory multiprocessor platform. The aim of the algorithm is to obtain a good binding that results in low makespans of the schedules of the DAGs.

Image-based control systems are becoming common in domains such as robotics, healthcare and industrial automation. Coping with a long sample period because of the latency of the image processing algorithm is an open challenge. Modern multi-core platforms allow to address this challenge by pipelining the sensing algorithm.

Cyber-Physical Systems (CPS) are tightly coupled with the environment, and therefore it is important that interactions with the surroundings like Human-Computer-Interactions are performed very responsive. Since CPS are often embedded without traditional input devices, like in medical or automotive contexts, gesture recognition approaches are emerging.

The design and analysis of smart system behavior needs to bridge between worlds – both with regard to engineering methods and to the technologies central to adaptivity and thus acore functionality of smart systems-of-systems. We illustrate this in our domain, smart buildings, where AI technologies like rule based or probabilistic reasoning set the strategies that define the building’s adaptive behavior, but control loops firmly set in control engineering implement it.

This paper proposes methods for verification of (m, k)-firmness properties of control applications running on a shared TDMA-scheduled processor. We particularly consider dropped samples arising from processor sharing. Based on the available processor budget for any sample that is ready for execution, the Finite-Point (FP) method is proposed for quantification of the maximum number of dropped samples.

We present an analysis method that provides tight temporal bounds for applications modeled by Synchronous Dataflow Graphs and mapped to shared resources. We consider the resource sharing effects on the temporal behaviour of the application by embedding worst case resource availability curves in the symbolic simulation of the application graph.

Today’s manufacturing systems are typically complex cyber-physical systems where the physical and control aspects interact with the scheduling decisions. Optimizing such facilities requires ordering jobs and configuring the manufacturing system for each job. This optimization problem can be described as a Multi-Objective Generalized TSP where conflicting objectives lead to a trade-off space.

A domain specific language (DSL) focuses on the essential concepts in a specific problem domain, and abstracts from low-level implementation details. The development of DSLs usually centers around the metamodel,grammar and code generator, possibly extended with transformations to analysis models. Typically, little attention is given to the formal semantics of the language, whereas this is essential for reasoning about DSL models, and for assessing the correctness of the generated code and analysis models.

Software maintenance consumes an increasing proportion of industrial software engineering budgets. Over time the technical debt grows, until it becomes unavoidable to rejuvenate the legacy software to a new design, while preserving the valuable domain logic. In this paper, we explore the feasibility of a model-based rejuvenation approach for use in an industrial context.

A domain specific language (DSL) abstracts from implementation details and is aligned with the way domain experts reason about a software component. The development of DSLs is usually centered around a grammar and transformations that generate implementation code or analysis models. The semantics of the language is often defined implicitly and in terms of a transformation to implementation code.