Abstract
Modern distributed real-time embedded applications have high processing requirements associated with strict deadlines. For some applications, such constraints cannot be fulfilled by existing single-core embedded platforms. A solution is to parallelize the execution of the applications, by allowing networked nodes to distribute their workload to remote nodes with spare capacity. In that context, this paper presents a holistic timing analysis for fixedpriority fork-join parallel/distributed tasks. Furthermore, we extend the holistic approach to consider the interaction between parallel threads and messages interchanged through a flexible time triggered switched Ethernet network, and we show how the pessimism on the worst case response time computation of such tasks can be reduced by considering the pipeline effect that occurs in such distributed systems. To evaluate the performance and correctness of the holistic model, this paper includes a numerical evaluation based on a real automotive application. The obtained results show that the proposed method is effective in distributing the load by different nodes, allowing a significant reduction of the worst case response time of the tasks. Moreover, the paper also reports an implementation of the model on a Linux library, called parallel/distributed real-time, as well as the corresponding results obtained on a real testbed. The obtained results are in accordance with the predictions of the holistic timing analysis.

Abstract
Smart grids play an important role in the modernization and optimization of the existing electrical grid, to accomplish the current European Union Energy and Climate targets. Smart grids require distributed applications to manage the grid more efficiently. The performance of the distributed applications impacts on the communications delay time and on the timely interaction with the devices located in the users' Home Area Networks. This paper presents the results of the ENCOURAGE project related to the development of a software platform to support smart grids. The work presented in this paper assesses four different middleware configurations and analyses the results on the delay performance tests. The results show that the mean end-to-end delay is between 310 ms and 453 ms in proper conditions. In terms of operational costs, the optimal configuration enables managing houses with less than 0.25 Euros per month per house. This paper justifies the maturity of the technology to support smart grids, and the possibility to transfer the ENCOURAGE project results to the industry.

Abstract
The need for maintenance is based on the wear of components of machinery. If this need can be defined reliably beforehand so that no unpredicted failures take place then the maintenance actions can be carried out economically with minimum disturbance to production. There are two basic challenges in solving the above. First understanding the development of wear and failures, and second managing the measurement and diagnosis of such parameters that can reveal the development of wear. In principle the development of wear and failures can be predicted through monitoring time, load or wear as such. Monitoring time is not very efficient, as there are only limited numbers of components that suffer from aging which as such is result of chemical wear i.e. changes in the material. In most cases the loading of components influences their wear. In principle the loading can be stable or varying in nature. Of these two cases the varying load case is much more challenging than the stable one. The monitoring of wear can be done either directly e.g. optical methods or indirectly e.g. vibration. Monitoring actual wear is naturally the most reliable approach, but it often means that additional investments are needed. The paper discusses the above issues and what are the requirements that follow from these for optimising maintenance based of the use of Cyber Physical Systems. © 2016 IEEE.

Abstract
The FlexOffer (FO) concept was initially created within the EU FP7 project MIRABEL [1]. It permits exposing demand and supply loads with associated flexibilities in time and quantity for energy commerce, load levelling, and different use-cases. To put it in a simple way, a FO specifies an amount of energy, a duration, an earliest begin time, a latest finish time, and a price, e.g., "I want 50 KWh over 3 hours between 5 PM and 12 PM, for a value of 0.25 €/kWh".

Abstract
Software transactional memory (STM) is a synchronisation paradigm which improves the parallelism and composability of modern applications executing on a multi-core architecture. However, to abort and retry a transaction multiple times may have a negative impact on the temporal characteristics of a real-time task set. This paper addresses this issue: It provides a framework in which an upper-bound on the worst-case response time of each task is derived, assuming that tasks are scheduled by following either the Non-Preemptive During Attempt (NPDA), Non-Preemptive Until Commit (NPUC) or Stack Resource Policy for Transactional Memory (SRPTM) policy.

Abstract
It is a known fact that processes running concurrently on different cores in a multicore environment interfere with each other on the processor shared resources. The contention on these shared resources considerably slows down the execution on every core since sometimes the cores must stall while their requests to access the resources are being served. But by how much the execution may be slowed down due to this interference? In this paper we answer this question with numbers coming from experimentation. That is, we quantify the magnitude of the impact of the interference on the execution time by running programs taken from the TACLeBench benchmark suite, a popular benchmark suite in the real-time research community, on the first generation of Kalray manycore processor family, the MPPA-256 (the development board) that goes by the codename "Andey". © Vincent Nélis, Patrick Meumeu Yomsi and Luís Miguel Pinho.