The application of decentralized approaces for Cyber-Physical Production Systems (CPPS) can be a significant step towards improving operational efficiency and adaptability in industrial production processes. This paper discusses the benefits of implementing a decentralized Monitor-Analyze-Plan-Execute and Knowledge (MAPE-K) framework on edge nodes in Cyber-Physical Production Systems (CPPS) for plant production. The study systematically reviews literature to analyze the strengths and limitations of decentralized approaches compared to centralized systems. It is shown that decentralized approaches offer improvements in data processing, lower latency, higher reliability, and bandwidth efficiency. The study demonstrates the importance of decentralized MAPE-K control loops in improving real-time data processing, reducing latency, and improving overall system reliability and bandwidth efficiency in smart farming environments. Furthermore, a decentralized approach offers benefits in terms of scalability, data protection, and resource optimization. However, the potential challenges related to resource constraints and security are also highlighted.

Bluetooth Low Energy (BLE) is a wireless communication technology for power-constrained Internet of Things (IoT) applications. BLE data can be transmitted via either the IPv6 or the Generic ATTribute (GATT) Profile protocol, with the former supporting dynamic IoT structures and the latter being application-friendly. In fact, GATT requires the data layout to be known in advance by peer devices, in order to properly interpret the received data. In this paper, we introduce DynGATT, a protocol that achieves the benefits of both IPv6 and GATT, by extending GATT in a seamless fashion to support dynamic IoT structures. The key idea of DynGATT is to use GATT descriptors, originally intended to specify data in static IoT scenarios, to also specify IoT systems whose structures may dynamically evolve. Peer devices reading these descriptors will know how to interpret the data of GATT characteristics provided by devices joining the IoT network. Because no additional data have to be transmitted, the connection time is then reduced with respect to classical BLE. DynGATT has been implemented and tested in an agricultural IoT application, with different types of sensor nodes. Our experimental evaluation shows that DynGATT is very power-efficient, despite its added flexibility. Its worst-case power consumption is only around 19.37 µA per data transmission and around 41.37 µA overall. This consumption can be further reduced by using the methods discussed in this paper. To the best of our knowledge, this work is the first to support dynamic IoT structures in a GATT-based setting.

The typical cell is a key concept for stochastic-geometry based modeling in communication networks, as it provides a rigorous framework for describing properties of a serving zone associated with a component selected at random in a large network. We consider a setting where network components are located on a large street network. While earlier investigations were restricted to street systems without preferred directions, in this paper we derive the distribution of the typical cell in Manhattan-type systems characterized by a pattern of horizontal and vertical streets, designed to model real cities with a gridlike layout. We explain how the mathematical description can be turned into a simulation algorithm, provide numerical results uncovering novel effects when compared to classical isotropic networks and finally compare the results to a real street system.

We study fundamental characteristics for the connectivity of multi-hop D2D networks. Devices are randomly distributed on street systems and are able to communicate with each other whenever their separation is smaller than some connectivity threshold. We model the street systems as Poisson-Voronoi or Poisson-Delaunay tessellations with varying street lengths. We interpret the existence of adequate D2D connectivity as percolation of the underlying random graph. We derive and compare approximations for the critical device-intensity for percolation, the percolation probability and the graph distance. Our results show that for urban areas, the Poisson Boolean Model gives a very good approximation, while for rural areas, the percolation probability stays far from 1 even far above the percolation threshold.

Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening inside the data-flow system.

With the need to make sense out of large and constantly growing information spaces, tools to support information management are becoming increasingly valuable. In prior work we proposed the "Visual Wiki" concept to describe and implement web-based information management applications. By focusing on the integration of two promising approaches, visualizations and collaboration tools, our Visual Wiki work explored synergies and demonstrated the value of the concept. Building on this, we introduce "VikiBuilder", a Visual Wiki meta-tool, which provides end-user supported modeling and automatic generation of Visual Wiki instances. We describe the design and implementation of the VikiBuilder including its architecture, a domain specific visual language for modeling Visual Wikis, and automatic generation of those. To demonstrate the utility of the tool, we have used it to construct a variety of different Visual Wikis. We describe the construction of Visual Wikis and discuss the strengths and weaknesses of our meta-tool approach.

This paper describes a software architecture documentation tool (KaitoroBase) built within the Thinkbase Visual Wiki to provide support for non-linear navigation and visualization of Software Architecture Documents (SADs) produced using the Attribute-Driven Design (ADD) method. This involves constructing the meta-model for the SAD in Freebase which provides the foundation for the graph-based interactive visualization enabled by Thinkbase. The resulting tool displays a graphical, high-level structure of SAD, allows for exploratory search, non-linear navigation, and at the same time connects to low-level details of SADs in a wiki.