Abstract
In this paper we analyze some of the existing solutions for Message-Oriented Middleware (MOM), which can be used on industrial environments, and that are, at the same time, capable of handling large quantities of data and of providing adequate Quality-of-Service (QoS) levels for its supported applications. We also make a proposal for the generic structure of a middleware layer supported on a MOM. © 2013 IEEE.

Abstract
Modern real-time embedded applications present high computation requirements which need to be realized within strict time constraints. The current trend towards parallel processing in the embedded domain allows providing higher processing power. However, in some embedded applications, the use of powerful enough multi-core processors, may not be possible due to energy, space or cost constraints. A solution for this problem is to extend the parallel execution of the applications, allowing them to distribute their workload among networked nodes, on peak situations, to remote neighbour nodes in the system. In this context, we present the Partitioned-Distributed- Deadline Monotonic Scheduling algorithm for fork-join parallel/distributed fixed-priority tasks. We study the problem of scheduling fork-join tasks that execute in a distributed system, where the inherent transmission delay of tasks must be considered and cannot be deemed negligible, as in the case of multicore systems. Our scheduling algorithm is shown to have a resource augmentation bound of 4, which implies that any task set that is feasible on m unit-speed processors and a single shared real-time network, can be scheduled by our algorithm on m processors and a single real-time network that are 4 times faster. We confirm through simulations our analytical results.

Abstract
In order to increase the efficiency in the use of energy resources, the electrical grid is slowly evolving into a smart(er) grid that allows users' production and storage of energy, automatic and remote control of appliances, energy exchange between users, and in general optimizations over how the energy is managed and consumed. One of the main innovations of the smart grid is its organization over an energy plane that involves the actual exchange of energy, and a data plane that regards the Information and Communication Technology (ICT) infrastructure used for the management of the grid's data. In the particular case of the data plane, the exchange of large quantities of data can be facilitated by a middleware based on a messaging bus. Existing messaging buses follow different data management paradigms (e.g.: request/response, publish/subscribe, data-oriented messaging) and thus satisfy smart grids' communication requirements at different extents. This work contributes to the state of the art by identifying, in existing standards and architectures, common requirements that impact in the messaging system of a data plane for the smart grid. The paper analyzes existing messaging bus paradigms that can be used as a basis for the ICT infrastructure of a smart grid and discusses how these can satisfy smart grids' requirements.

Abstract
This paper presents a holistic timing analysis for fixed-priority fork-join Parallel/Distributed tasks (P/D tasks) over a Flexible Time Triggered - Switched Ethernet (FTT-SE) network. The holistic approach considers both time-triggered and event-triggered tasks/messages.

Abstract
In this paper, we propose the Distributed using Optimal Priority Assignment (DOPA) heuristic that finds a feasible partitioning and priority assignment for distributed applications based on the linear transactional model. DOPA partitions the tasks and messages in the distributed system, and makes use of the Optimal Priority Assignment (OPA) algorithm known as Audsley's algorithm, to find the priorities for that partition. The experimental results show how the use of the OPA algorithm increases in average the number of schedulable tasks and messages in a distributed system when compared to the use of Deadline Monotonic (DM) usually favoured in other works. Afterwards, we extend these results to the assignment of Parallel/Distributed applications and present a second heuristic named Parallel-DOPA (P-DOPA). In that case, we show how the partitioning process can be simplified by using the Distributed Stretch Transformation (DST), a parallel transaction transformation algorithm introduced in [1].

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.