Abstract
The advent of next-generation many-core embedded platforms has the chance of intercepting a converging need for predictable high-performance coming from both the High-Performance Computing (HPC) and Embedded Computing (EC) domains. On one side, new kinds of HPC applications are being required by markets needing huge amounts of information to be processed within a bounded amount of time. On the other side, EC systems are increasingly concerned with providing higher performance in real-time, challenging the performance capabilities of current architectures. This converging demand, however, raises the problem about how to guarantee timing requirements in presence of parallel execution. This paper presents the approach of project P-SOCRATES for the design of an integrated framework for the execution of workload-intensive applications with real-time requirements on top of nextgeneration commercial-off-the-shelf (COTS) platforms based on many-core accelerated architectures. The time-criticality and parallelisation challenges are addressed by merging techniques coming from both HPC and EC domains, identifying the main sources of indeterminism and proposing efficient mapping and scheduling algorithms, along with the associated timing and schedulability analysis, to guarantee the real-time and performance requirements of the applications.

Abstract

Abstract
Recent embedded processor architectures containing multiple heterogeneous cores and non-coherent caches, bring renewed attention to the use of Software Transactional Memory (STM) as a building block for developing parallel applications. STM promises to ease concurrent and parallel software development, but relies on the possibility of abort conflicting transactions to maintain data consistency, which affects the execution time of tasks carrying transactions. Thus, execution time overheads resulting from aborts must be limited, otherwise the timing behaviour of the task set will not be predictable. In this paper we formalise a FIFO-based algorithm to order the sequence of commits of concurrent transactions. Furthermore, we propose and evaluate two non-preemptive scheduling strategies, in order to avoid transaction starvation. © 2014 Springer International Publishing Switzerland.

Abstract
Several methodologies have been proposed in the last decades to improve the quality of Safety-Critical Embedded Systems (SCES) and, at the same time, keep costs and schedule compatible with project plans. In particular, approaches such as Product Line Engineering (PLE) and Model-Driven Engineering (MDE) offer an interesting solution to reduce development complexity and time to market due to their synergy and common goals. However, the current state of how MDE and PLE can be combined to enhance productivity in the domain of SCES is not clear yet. This paper presents a systematic literature review, with the purpose of obtaining the state of the art of the aproaches, methods and methodologies whose goal is the combination of PLE and MDE for the development of SCES, and to verify the existence of empirical studies that demonstrate the application of these techniques in this type of development. We drew the following conclusions from the review results: (1) The number of studies using PLE with MDE to build SCES is relatively small, but has increased gradually in recent years. (2) The approaches diverge about what is needed to build Model-driven Product Lines. (3) Most of the approaches do not consider to differentiate between hardware and software variabilities. (4) Most of the studies propose the use of UML and feature diagrams. (5) The studies present case studies implemented in different tools and most of them are free. (6) The approaches do not cover the entire development lifecycle.

Abstract
The development of Critical Embedded Systems (CES) like Unmanned Aerial Vehicles (UAV) is complex because it needs to ensure a high degree of quality, with affordable cost and delivery time. It is also necessary to ensure security since failures in this type of system can lead to catastrophic results. In this sense, a Model-Driven Development (MDD) approach presents itself as a good alternative to the traditional development because coding complexity will be reduced by the use of high level models. In addition, it avoids the introduction of coding errors by human programmers, since the critical code will be built automatically through models transformation. From another perspective, Embedded Systems Development can benefit from Software Engineering techniques like Product Lines to reduce costs and time-to-market. While other works propose the use of Product Line techniques to improve Embedded Software development, we propose a Product Line approach to the whole Critical Embedded System development life cycle, including hardware variability management. Therefore, this paper proposes a Critical Embedded System Product Line Model Based approach, which aims to reduce the above mentioned challenges. The development approach proposes a Domain Engineering and Application Engineering focused on the system, with both software and hardware. To illustrate the proposed approach we include some artifacts from a case study in the UAV domain.

Abstract
While Cluster-Tree network topologies look promising for WSN applications with timeliness and energy-efficiency requirements, we are yet to witness its adoption in commercial and academic solutions. One of the arguments that hinder the use of these topologies concerns the lack of flexibility in adapting to changes in the network, such as in traffic flows. This paper presents a solution to enable these networks with the ability to self-adapt their clusters' duty-cycle and scheduling, to provide increased quality of service to multiple traffic flows. Importantly, our approach enables a network to change its cluster scheduling without requiring long inaccessibility times or the re-association of the nodes. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs without significant changes to the protocol. Finally, we analyze and demonstrate the validity of our methodology through a comprehensive simulation and experimental validation using commercially available technology on a Structural Health Monitoring application scenario.