Context-aware adaptation in DySCAS

DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met

A global generic architecture for the future Internet of Things

The envisioned 6A Connectivity of the future IoT aims to allow people and objects to be connected anytime, anyplace, with anything and anyone, using any path/network and any service. Because of heterogeneous resources, incompatible standards and communication patterns, the current IoT is constrained to specific devices, platforms, networks and domains. As the standards have been accepted worldwide, most existing IoT platforms use Web Services to integrate heterogeneous devices. Human-readable protocols of Web Services cause non-negligible overhead for object-to-object communication. Other issues, such as: lack of applications and modularized services, high cost of devices and software development also hinder the common use of the IoT. In this paper, a global generic architecture for the future IoT (GGIoT) is proposed to meet the envisioned 6A Connectivity of the future IoT. GGIoT is independent of particular devices, platforms, networks, domains and applications, and it minimizes transmission message size to fit devices with minimal capabilities, such as passive RFID tags. Thus, lower physical size and cost are possible, and network overhead can be reduced. The proposed GGIoT is evaluated via performance analysis and proof-of-concept case studies

Model-Based Engineering of Collaborative Embedded Systems

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years

An approach to open virtual commissioning for component-based automation

Increasing market demands for highly customised products with shorter time-to-market and at lower prices are forcing manufacturing systems to be built and operated in a more efficient ways. In order to overcome some of the limitations in traditional methods of automation system engineering, this thesis focuses on the creation of a new approach to Virtual Commissioning (VC). In current VC approaches, virtual models are driven by pre-programmed PLC control software. These approaches are still time-consuming and heavily control expertise-reliant as the required programming and debugging activities are mainly performed by control engineers. Another current limitation is that virtual models validated during VC are difficult to reuse due to a lack of tool-independent data models. Therefore, in order to maximise the potential of VC, there is a need for new VC approaches and tools to address these limitations. The main contributions of this research are: (1) to develop a new approach and the related engineering tool functionality for directly deploying PLC control software based on component-based VC models and reusable components; and (2) to build tool-independent common data models for describing component-based virtual automation systems in order to enable data reusability. [Continues.

Design of an autonomous software platform for future symbiotic service management

Nowadays, public as well as private communication infrastructures are all contending for the same limited amount of bandwidth. To optimally share network resources, symbiotic networks have been proposed, which cross logical and physical boundaries to improve the reliability, scalability, and energy efficiency of the network as a whole as well as its constituents. This paper focuses on software services in such symbiotic networks. We propose a platform for the intelligent composition of services provided by symbiotically connected parties, resulting in novel cooperation opportunities. The platform harvests Semantic Web technology to describe services in a highly expressive manner, and constructs service compositions using SeCoA, our tunable best-first search algorithm. The resulting compositions are then enacted via CaPI, a reconfigurable middleware infrastructure. By means of an illustrative scenario, we provide further insight into the platform's functioning

Achieving Autonomic Computing through the Use of Variability Models at Run-time

Increasingly, software needs to dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing infrastructure and in the surrounding physical environment. Adaptability is emerging as a necessary underlying capability, particularly for highly dynamic systems such as context-aware or ubiquitous systems. By automating tasks such as installation, adaptation, or healing, Autonomic Computing envisions computing environments that evolve without the need for human intervention. Even though there is a fair amount of work on architectures and their theoretical design, Autonomic Computing was criticised as being a \hype topic" because very little of it has been implemented fully. Furthermore, given that the autonomic system must change states at runtime and that some of those states may emerge and are much less deterministic, there is a great challenge to provide new guidelines, techniques and tools to help autonomic system development. This thesis shows that building up on the central ideas of Model Driven Development (Models as rst-order citizens) and Software Product Lines (Variability Management) can play a signi cant role as we move towards implementing the key self-management properties associated with autonomic computing. The presented approach encompass systems that are capable of modifying their own behavior with respect to changes in their operating environment, by using variability models as if they were the policies that drive the system's autonomic recon guration at runtime. Under a set of recon guration commands, the components that make up the architecture dynamically cooperate to change the con guration of the architecture to a new con guration. This work also provides the implementation of a Model-Based Recon guration Engine (MoRE) to blend the above ideas. Given a context event, MoRE queries the variability models to determine how the system should evolve, and then it provides the mechanisms for modifying the system.Cetina Englada, C. (2010). Achieving Autonomic Computing through the Use of Variability Models at Run-time [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7484Palanci