The demand for computing power and performance in real-time embedded systems is continuously increasing since new customer requirements and more advanced features are appearing every day. To support these functionalities and handle them in a more efficient way, multi-core computing platforms are introduced. These platforms allow for parallel execution of tasks on multiple cores, which in addition to its benefits to the system's performance introduces a major problem regarding the timing predictability of the system. That problem is reflected in unpredictable inter-core interferences, which occur due to shared resources among the cores, such as the system bus. This thesis investigates the application of different optimization techniques for the offline scheduling of tasks on the individual cores, together with a global scheduling policy for the access to the shared bus. The main effort of this thesis focuses on optimizing the inter-core data propagation delays which can provide a new way of creating optimized schedules. For that purpose, Constraint Programming optimization techniques are employed and a Phased Execution Model of the tasks is assumed. Also, in order to enforce end-to-end timing constraints that are imposed on the system, job-level dependencies are generated prior and subsequently applied during the scheduling procedure. Finally, an experiment with a large number of test cases is conducted to evaluate the performance of the implemented scheduling approach. The obtained results show that the method is applicable for a wide spectrum of abstract systems with variable requirements, but also open for further improvement in several aspects.

Software systems in the automotive domain are generally safety critical and subject to strict timing requirements. Systems of this character are often constructed utilizing periodically executed tasks, that have a hard deadline. In addition, these systems may have additional deadlines that can be specified on cause-effect chains, or simply task chains. They are defined by existing tasks in the system, hence the chains are not stand alone additions to the system. Each chain provide an end-to-end timing constraint targeting the propagation of data through the chain of tasks. These constraints specify the additional timing requirements that need to be fulfilled, when searching for a valid schedule. In this thesis, an offline non-preemptive scheduling method is presented, designed for single core systems. The scheduling problem is defined and formulated utilizing Constraint Programming. In addition, to ensure that end-to-end timing requirements are met, job-level dependencies are considered during the schedule generation. Utilizing this approach can guarantee that individual task periods along with end-to-end timing requirements are always met, if a schedule exists. The results show a good increase in schedulability ratio when utilizing job-level dependencies compared to the case where job-level dependencies are not specified. When the system utilization increases this improvement is even greater. Depending on the system size and complexity the improvement can vary, but in many cases it is more than double. The scheduling generation is also performed within a reasonable time frame. This would be a good benefit during the development process of a system, since it allows fast verification when changes are made to the system. Further, the thesis provide an overview of the entire process, starting from a system model and ending at a fully functional schedule executing on a hardware platform.

Research into modular approaches for constructing power electronics control systems has provided a number of benefits, as well as new opportunities. Control systems composed of an interconnected collection of standardized parts makes distributed processing a realistic possibility. Unfortunately, current strategies to supporting software on such systems have a number of critical drawbacks. Many existing approaches rely on centralized control strategies, fail to support fault tolerance in the face of failures among processing nodes or communications links, and fail to robustly support live addition or removal of nodes from a running network. In this context, failure of a single element means failure of the entire system. This thesis describes research to extend the Dataflow Architecture Real-time Kernel (DARK) to support distributed, fault-tolerant execution of control algorithms for power electronics control systems. An appropriate scheme for fault-tolerant scheduling of processes on distributed processing nodes is described, added to DARK, and evaluated. Literature indicates that fault-tolerant multiprocessor scheduling for hard real-time tasks with task precedence constraints is an NP-hard problem. The new system is based on an off-line fault-tolerant scheduling strategy that generates a static schedule of tasks for each processing unit to follow. This algorithm handles both the task precedence constraints and the constraints imposed by the underlying network protocol(DRPESNET). Modifications to the underlying daisy-chained, packet-switched, time-triggered ring network protocol to support communications fault tolerance and plug-and-play addition or removal of live nodes from an existing control system are also described. / Master of Science