Abstract
This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Abstract
The Arrowhead project aims to address the technical and applicative issues associated with cooperative automation based on Service Oriented Architectures. The problems of developing such kind of systems are mainly due to the lack of adequate development and service documentation methodologies, which would ease the burden of reusing services on different applications. The Arrowhead project proposes a technical framework to efficiently support the development of such systems, which includes several tools for documentation of services and to support the development of SOA-based installations. The work presented in this paper describes the approach which has been developed for the first generation pilots to support the documentation of their structural services. Each service, system and system-of-systems within the Arrowhead Framework must be documented and described in such way that it can be implemented, tested and deployed in an interoperable way. This paper presents the first steps of realizing the Arrowhead vision for interoperable services, systems and systems-of-systems.

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
Industrial processes use energy to transform raw materials and intermediate goods into final products. Many efforts have been done on the minimization of energy costs in industrial plants. Apart from working on "how" an industrial process is implemented, it is possible to reduce the energy costs by focusing on "when" it is performed. Although, some manufacturing plants (e.g. refining or petrochemical plants) can be inflexible with respect to time due to interdependencies in processes that must be respected for performance and safety reasons, there are other industrial segments, such as alumina plants or discrete manufacturing, with more degrees of flexibility. These manufacturing plants can consider a more flexible scheduling of the most energy-intensive processes in response to dynamic prices and overall condition of the electricity market. In this scenario, requests for energy can be encoded by means of a formal structure called flex-offers, then aggregated (joining several flex-offers into a bigger one) and sent to the market, scheduled, disaggregated and transformed into consumption plans, and eventually, into production schedules for given industrial plant. In this paper, we describe the flex-offer concept and how it can be applied to industrial and home automation scenarios. The architecture proposed in this paper aims to be adaptable to multiples scenarios (industrial, home and building automation, etc.), thus providing the foundations for different concept implementations using multiple technologies or supporting various kinds of devices.

Abstract
Runtime verification is an emerging discipline that investigates methods and tools to enable the verification of program properties during the execution of the application. The goal is to complement static analysis approaches, in particular when static verification leads to the explosion of states. Non-functional properties, such as the ones present in real-time systems are an ideal target for this kind of verification methodology, as are usually out of the range of the power and expressiveness of classic static analyses. In this paper, we present a framework that allows real-time programs written in Ada to be augmented with runtime verification capabilities. Our framework provides the infrastructures which is needed to instrument the code with runtime monitors. These monitors are responsible for observing the system and reaching verdicts about whether its behavior is compliant with its non-functional properties. We also sketch a contract language to extend the one currently provided by Ada, with the long term goal of having an elegant way in which runtime monitors can be automatically synthesized and instrumented into the target systems. The usefulness of the proposed approach is demonstrated by showing its use for an application scenario.

Abstract
Runtime Monitoring of hard real-time embedded systems is a promising technique for ensuring that a running system respects timing constraints, possibly combined with faults originated by the software and/or hardware. This is particularly important when we have real-time embedded systems made of several components that must combine different levels of criticality, and different levels of correctness requirements. This paper introduces a compositional monitoring framework coupled with guarantees that include time isolation and the response time of a monitor for a predicted violation. The kind of monitors that we propose are automatically generated by synthesizing logic formulas of a timed temporal logic, and their correctness is ensured by construction.