Our everyday lives are increasingly pervaded by digital assistants and smart devices forming the Internet of Things (IoT). While user interfaces to directly monitor and control individual IoT devices are becoming more sophisticated and end-user friendly, applications to connect standalone IoT devices and create more complexIoT processesfor automating and assisting users with repetitive tasks still require a high level of technical expertise and programming knowledge. Related approaches for process modelling in IoT mostly suggest extensions to complex modelling languages, require high levels of abstraction and technical knowledge, and rely on unintuitive tools. We present a novel approach for end-user oriented-no-code-IoT process modelling using Mixed Reality (MR) technology:HoloFlows. Users are able to explore the IoT environment and model processes among sensors and actuators as first-class citizens by simply “drawing” virtual wires among physical IoT devices. MR technology hereby facilitates the understanding of the physical contexts and relations among the IoT devices and provides a new and more intuitive way of modelling IoT processes. The results of a user study comparing HoloFlows with classical modelling approaches show an increased user experience and decrease in required modelling knowledge and technical expertise to create IoT processes.

Plenty of novel emerging technologies are being proposed and evaluated today, mostly at the device and circuit levels. It is unclear what the impact of different new technologies at the system level will be. What is clear, however, is that new technologies will make their way into systems and will increase the already high complexity of heterogeneous parallel computing platforms, making it ever so difficult to program them. This paper discusses a programming stack for heterogeneous systems that combines and adapts well-understood principles from different areas, including capability-based operating systems, adaptive application runtimes, dataflow programming models, and model checking. We argue why we think that these principles built into the stack and the interfaces among the layers will also be applicable to future systems that integrate heterogeneous technologies. The programming stack is evaluated on a tiled heterogeneous multicore.

The miniaturization and modularization of production capacity brings with it not only greater agility and efficiency, but also increased flexibility in the form of mobility. This flexibility allows production capacity to be moved when and where it is most needed, generating new business opportunities, e.g., allowing modular units to be rented, leased, or shared. This flexibility, however, requires information and control systems that ensure a correct and secure flow of information between different stakeholders of the supply chain. Based on this, the present article characterizes the concept of software-defined mobile supply chains, presenting its main requirements, opportunities, and limitations. In addition, we present two case studies in which the proposed concept is evaluated in order to demonstrate its applicability. Here, due to the new optimization problems that arise when considering mobile facilities, special interest is given to the planning and control of the required operations, as well as the difficulties associated with the exchange of physical and intellectual assets between different stakeholders.