Abstract
Developing real-time systems applications requires programming paradigms that can handle the specification of concurrent activities and timing constraints, and controlling execution on a particular platform. The increasing need for high-performance, and the use of fine-grained parallel execution, makes this an even more challenging task. This paper explores the state-of-the-art and challenges in real-time parallel application development, focusing on two research directions: one from the high- performance domain (using OpenMP) and another from the real-time and critical systems field (based on Ada). The paper reviews the features of each approach and highlights remaining open issues.

Abstract
Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

Abstract
The Internet of Things (IoT) enables everyday objects to connect and communicate remotely, transforming areas such as smart homes and industrial automation. IoT systems can be standalone or interconnected in a System of Systems, where multiple devices work together towards a common goal. A key application is Energy Monitoring Systems (EMS), which track energy use within communities, using energy production and consumption. Designing this type of IoT systems remains complex and requires careful consideration of heterogeneous devices, their limitations, software, communication protocols, data management, and security. This paper presents a design approach for EMS communities, with a focus on house-level IoT systems. We introduce a model-driven development methodology, a holistic and flexible framework for designing IoT systems across the development and operations lifecycle. Especially, the concept of projectors enables an easy shift between domain assets and provide automation support. The approach is validated with a real-life use case, for which an analysis phase was developed, showing the benefits of using our approach for managing EMS and the automation of the analysis configuration. © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

Abstract
The Constant Bandwidth Server (CBS) is a mechanism used in real-time systems to enable aperiodic soft realtime tasks with unknown execution parameters to run under a dynamic scheduling policy such as Earliest Deadline First (EDF), while still ensuring schedulability by using a bandwidth reservation strategy. This paper proposes an approach to extend the Zephyr open-source real-time operating system, currently maintained by the Linux Foundation, to support aperiodic tasks with CBS. The paper provides the proposed architecture and the design and implementation of the CBS mechanisms in the operating system, which are then evaluated in two test cases in an embedded platform. © 2025 Elsevier B.V., All rights reserved.