Scientific publications

When software components are developed iteratively, code frequently evolves in an inductive manner: A unit is created and is then copied and modified many times. Such development often happens when variation points and, hence, proper domain abstractions are initially unclear. As a result, there may be substantial amounts of code duplication, and the code may be difficult to understand and maintain, warranting a redesign.

Energy efficiency is of paramount importance in designing low-power wireless sensor nodes. Approximate computing is a new circuit-level technique for reducing power consumption. However, the gain in power by applying this technique is achieved at the cost of computational errors. The impact of such inaccuracies in the circuit level of a radio transceiver chip on the performance of Wireless Sensor Networks has not yet been explored.

In multi-media applications, bufers represent storage spaces that are used to store the data communicated between diferent tasks in the application, and throughput refers to the rate at which output data is produced by the application. The capacities of the bufers inluence the throughput, by altering the waiting times for tasks that need to read or write data from or to the bufers.

Vehicle platooning has gained attention for its potential to achieve an increased road capacity and safety, and a higher fuel efficiency. Member vehicles of a platoon wirelessly communicate complying with industrial standards such as IEEE 802.11p. By exchanging information with other members via wireless communication, a platoon member computes its desired acceleration which is then passed on to the engine control system via in-vehicle network to physically realize the acceleration.

Maintaining legacy software is one of the most common struggles of the software industry, being costly yet essential. We tackle that problem by providing better understanding of software by extracting behavioural models using the model learning technique. The used technique interacts with a running component and extracts abstract models that would help developers make better informed decisions.

Image-Based Control (IBC) systems have a long sample period. Sensing in these systems consists of compute-intensive image processing algorithms whose response times are dependent on image workload. IBC systems are typically designed for the worst-case workload that results in a long sample period and hence suboptimal quality-of-control (QoC).

We develop a model-based approach to predict timing of service-based software applications on Linux-based multi-core platforms for alternative mappings (affinity and priority settings). Service-based applications consist of communicating sequential (Linux) processes. These processes execute functions (also called services), but can only execute them one at a time.

Feedback control applications are robust to occasional deadline misses. This opens up the possibility of saving scarce (computation and communication) resources on embedded platforms. Stability and performance requirements of a control loop impose restrictions on acceptable patterns of deadline misses (e.

High-end manufacturing systems are cyber-physical systems where productivity depends on the close cooperation of mechanical (physical) and scheduling (cyber) aspects. Mechanical and control constraints impose minimal and maximal time differences between events in the product flow. Sequence-dependent constraints are used by a scheduler to optimize system productivity while satisfying operational requirements.

(m, k)-firm real-time tasks must meet the deadline of at least m jobs out of any k consecutive jobs to satisfy the firmness requirement. Scheduling of an (m, k)-firm task requires firmness analysis, whose results are used to provide system-level guarantees on the satisfaction of firmness conditions. We address firmness analysis of an (m, k)-firm task that is intended to be added to a set of asynchronous tasks scheduled under a Static-Priority Preemptive (SPP) policy.