Abstract
This paper presents an architecture that supports Quality of Service (QoS) in an Arrowhead-compliant System of Systems (SoS). The Arrowhead Framework supports local cloud functionalities for automation applications, provided by means of a Service Oriented Architecture (SOA), by offering a number of services that ease application development. On such applications the QoS guarantees are required for service fruition, and are themselves requested as services from the framework. To fulfil this objective we start by describing the Arrowhead architecture and the components needed to dynamically in run-time negotiate a system configuration that guarantees the QoS requirements between application services.

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
This paper presents an architecture that supports Quality of Service (QoS) in an Arrowhead-compliant System of Systems (SoS). The Arrowhead Framework supports local cloud functionalities for automation applications, provided by means of a Service Oriented Architecture (SOA), by offering a number of services that ease application development. On such applications the QoS guarantees are required for service fruition, and are themselves requested as services from the framework. To fulfil this objective we start by describing the Arrowhead architecture and the components needed to dynamically in run-time negotiate a system configuration that guarantees the QoS requirements between application services. © 2016 IEEE.

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.

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 parallelise 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 (P/D tasks). Furthermore, we extend the holistic approach to consider the interaction between parallel threads and messages interchanged through a Flexible Time Triggered - Switched Ethernet (FTT-SE) 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. © 2016 IEEE.

Abstract
The Arrowhead Framework is a European effort that aims to apply Service Oriented Architecture to the embedded systems' world. The Event Handler system is a component that supports the handling of events, and in that sense it enriches service-oriented applications with the capabilities of interacting via the publish/subscribe paradigm. In fact, the Event Handler system is in charge of the notification of events that occur in a given Arrowhead compliant installation, manages producers and consumers of events, allows filtering of messages, and manages historical data regarding events. This latter capability is performed either on local files, on a database, or through another component of the Arrowhead Framework - the Historian system. The net result of the integration of the Event Handler in an Arrowhead Framework simplifies and empowers the communication of its components, as it is demonstrated in the paper with two examples: the management of application faults, and the support to quality of service of orchestrated services.