A Practical Comparison of Scheduling Algorithms for Mixed Criticality Embedded Systems

With the consolidation of automotive control processes onto single highperformance ECUs the issue of running, and thus scheduling, processes of varying criticality on a single CPU has moved to the fore. This has resulted in a number of new algorithms for scheduling such systems, for example Adaptive Mixed Criticality (AMC). This project attempts to measure the performance of some of these algorithms on a singlecore embedded system CPU and compares them in order to shed some light on their different advantages and disadvantages

Securing Real-Time Internet-of-Things

Modern embedded and cyber-physical systems are ubiquitous. A large number of critical cyber-physical systems have real-time requirements (e.g., avionics, automobiles, power grids, manufacturing systems, industrial control systems, etc.). Recent developments and new functionality requires real-time embedded devices to be connected to the Internet. This gives rise to the real-time Internet-of-things (RT-IoT) that promises a better user experience through stronger connectivity and efficient use of next-generation embedded devices. However RT- IoT are also increasingly becoming targets for cyber-attacks which is exacerbated by this increased connectivity. This paper gives an introduction to RT-IoT systems, an outlook of current approaches and possible research challenges towards secure RT- IoT frameworks

Integration and validation of embedded flight software on space-qualified multicore architectures

In the recent decades, the importance of software on space missions has notably increased, reflecting the need to integrate advanced on-board functionalities. With multicore processors being lately introduced to host critical high-performance applications, the complexity to validate software has significantly raised with respect to single core architectures. While there has been a big step forward in avionics after the publication of the CAST-32A paper, the ECSS-E-ST-40C software engineering standard used by the European Space Agency (ESA) is still not providing validation support for multicore processors. Hence, it is expected that standardising guidelines to develop software on such platforms will become a recurring topic in the industry to match the demands of future space exploration missions

Evaluation of the parallel computational capabilities of embedded platforms for critical systems

Modern critical systems need higher performance which cannot be delivered by the simple architectures used so far. Latest embedded architectures feature multi-cores and GPUs, which can be used to satisfy this need. In this thesis we parallelise relevant applications from multiple critical domains represented in the GPU4S benchmark suite, and perform a comparison of the parallel capabilities of candidate platforms for use in critical systems. In particular, we port the open source GPU4S Bench benchmarking suite in the OpenMP programming model, and we benchmark the candidate embedded heterogeneous multi-core platforms of the H2020 UP2DATE project, NVIDIA TX2, NVIDIA Xavier and Xilinx Zynq Ultrascale+, in order to drive the selection of the research platform which will be used in the next phases of the project. Our result indicate that in terms of CPU and GPU performance, the NVIDIA Xavier is the highest performing platform