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
Introduction In this chapter, we present a number of applications of the Arrowhead Framework with special attention to services related to awareness and optimisation of energy consumption. First, we present the notion of FlexOffers as a general mechanism for describing energy flexibility. FlexOffers can be aggregated into larger flexibility units to be used as an Arrowhead service in the virtual market of energy [1]. This is followed by two examples on how to exploit such a flexibility service in the energy management of heat pumps and a campus building. Then we present two examples on how to exploit renewable energy to provide elevator services. Next, two examples of context aware services are described - smart lighting and smart car heating, and finally it is described how the Arrowhead Framework can play a role in the optimisation of municipal service systems. In the final section, we indicate future work. © 2017 by Taylor & Francis Group, LLC.

Abstract
Introduction In previous chapters local automation clouds and a SOA based architecture supporting the design and implementation of IoT based automation systems were discussed. This chapter is devoted to design and implementation of application services: •Design of an Arrowhead Framework system •Implementation of such a system and its services •Interoperability test 5.2 Application service design This section will discuss the design of an automation application system and associated services. For this purpose, we will make use of the simple control loop example addressing the level in a flotation tank. © 2017 by Taylor & Francis Group, LLC.

Abstract
Introduction In Chapter 2 local clouds were discussed followed by a local cloud automation architecture in Chapter 3. The automation architecture supports the implementation of local automation clouds. Such implementation is supported by the Arrowhead Framework and its core systems and services. © 2017 by Taylor & Francis Group, LLC.

Abstract
Embedded computers such as Raspberry Pi are gaining market as they offer considerable computation power on a flexible platform that can run different operating systems and user level libraries. There are a number of contributions on building middleware for connecting devices based on embedded computers in various ways; however, the temporal behavior of these systems has not been sufficiently covered, despite the fact that this is essential to validate the system design, operation, and timeliness that is needed in domains such as cyber-physical systems (CPS). This paper analyzes the temporal behavior of the connection among embedded computers and servers in the context of time sensitive deployments where some nodes can be virtualized offering mixed criticality execution platforms. We provide a scheme for using the Data Distribution Service standard to connect embedded computers based on Raspberry Pi and servers to analyze the temporal response stability.