Scientific publications

This paper proposes a modeling approach to capture the mapping of an application on a platform. The approach is based on Scenario-Aware Dataflow (SADF) models. In contrast to the related work, we express the complete design-space in a single formal SADF model. This allows us to have a compact and explorable state-space linked with an executable model capable of symbolically analyzing different mappings for their timing behavior.

Constructing a model of a system for model-based testing, simulation, or model checking can be cumbersome for existing, third party, or legacy components. Active automata learning, a form of black-box reverse engineering, and in particular Angluin’s L⋆ algorithm, support the automatic inference of a model from a System Under Learning (SUL), through observations and tests.

Accurate link quality estimation is an important building block in quality aware routing. In an inherently lossy, unreliable and dynamic medium such as wireless, the task of accurate estimation becomes very challenging. Over the years ETX has been widely used as a reliable link quality estimation metric.

Service-oriented systems are designed for interconnecting with other systems. The provided services face timing constraints, the so-called latencies. We present a high-level performance evaluation technique that can be used by a system designer to obtain distributions of these latencies. This technique is capable of capturing nondeterministic, probabilistic and real-time aspects in one go.

Cross-technology interference on the license-free ISM bands has a major negative effect on the performance of Wireless Sensor Networks (WSNs). Channel hopping has been adopted in the Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4e to eliminate blocking of wireless links caused by external interference on some frequency channels.

Cyber-Physical Systems (CPS) play an important role in the modern high-tech industry. Designing such systems is a challenging task due to the multi-disciplinary nature of these systems, and the range of abstraction levels involved. To facilitate hands-on experience with such systems, we develop a cyber-physical platform that aids in research and education on CPS.

This work proposes a Multi-Constraint Resource Allocation (MuCoRA) method for applications from multiple domains onto multi-processors. In particular, we address a mapping problem for multiple throughput-constrained streaming applications and multiple latency-constrained feedback control applications onto a multi-processor platform running under a Time-Division Multiple-Access (TDMA) policy.

We are currently confronted with a trend of increased pressure on health care, with associated increasing financial costs, due to an aging society and the expected increase in the prevalence of disability and chronic disease. Finding measures for cost reduction, without sacrificing quality of care, is a significant healthcare challenge.

General purpose platforms are characterized by unpredictable timing behavior. Real-time schedules of tasks on general purpose platforms need to be robust against variations in task execution times. We define robustness in terms of the expected number of tasks that miss deadlines. We present an iterative robust scheduler that produces robust multiprocessor schedules of directed acyclic graphs with a low expected number of tasks that miss their deadlines.

Development of high-level supervisory controllers is an important challenge in the design of high-tech systems. It has become a significant issue due to increased complexity, combined with demands for verified quality, time to market, ease of development, and integration of new functionality. To deal with these challenges, model-based engineering approaches are suggested as a cost-effective way to support easy adaptation, validation, synthesis, and verification of controllers.