This study investigates the targeted interference (TI) on the orthogonal frequency-division multiplexing (OFDM)-based physical channels in 5G new radio (NR) technology from the aspect of signal processing. Disrupting the orthogonality property between subcarriers (SCs) is considered as one of the destructive targets in OFDM based generations. Focusing on the orthogonality property, we propose a method to detect the disrupted subcarriers, and then neutralize the TI using a multiplicative signal. This signal is designed to counteract the phase and amplitude distortions introduced by the interferer, effectively restoring the orthogonality of the affected subcarriers. Thanks to studying the frequency aspect of the disrupted signal, the proposed method is independent of the interferers’ transmitted power. Simulation results evaluate the detection performance of the proposed method with various numbers of OFDM subcarriers. This study provides actionable insights for 5G NR network operators and equipment manufacturers to enhance the resilience of their systems against targeted threats, contributing to more reliable and secure 5G deployments.

With the increasing adoption of 5G networks in smart cities and Industry 4.0 applications, energy efficiency (EE) has become a critical concern, particularly for industrial Internet of Things (IIoT) devices that operate continuously in latency-sensitive environments. This paper presents a novel Paging Signal-Aware Ordered Statistical Decoding (PS-Aware OSD) algorithm to optimize energy use during paging operations. By intelligently predicting paging occasions (PO) based on historical patterns, the algorithm reduces unnecessary wake-ups in extended discontinuous reception (eDRX) cycles. Simulations demonstrate that this approach improves energy efficiency by up to 40%, reduces block error rate (BLER), and improves throughput and latency compared to standard third-generation partnership project (3GPP) paging techniques. The paper discusses practical implementation aspects, acknowledges system limitations, and proposes future work, including the integration of machine learning for dynamic paging optimization and the development of security measures against spoofing or unnecessary battery drain.

In this paper, the use of Large Language Models (LLMs) for the configuration of hybrid TSN/5G networks is investigated. We discuss promising use cases where LLMs offer significant potential to simplify complex configuration tasks. Particularly, we consider two important scenarios: In the first scenario, the LLM functions as an engineering component enhancing traditional network control entities such as the Centralized User Configurations (CUCs) and Centralized Network Configurations (CNCs) of TSN networks and interacting with the 5G control plane. In the second scenario, the LLM serves as an interactive assistance tool for users performing manual configuration tasks. For these use cases, an LLM-based architecture for network configuration is proposed, which consists of a Retrieval-Augmented Generation (RAG) system, a verification component, and an orchestration layer. Within the framework of this architecture, we introduce LLM-based methods to enhance the reliability of configuration in complex real-time networks, leveraging strategies such as divide and conquer, prompt engineering, and verification.

The overall Industry 4.0 developments and the highly dynamic threat landscape enhance the need for continuous security engineering of industrial components, modules, and systems. Security risk assessments play a major role to ensure a secure operation of Industrial Automation and Control Systems (IACSs) but are often neglected due to missing resources and a lack of human experts for the sophisticated manual tasks. To relieve this situation and to increase the degree of automation of security risk assessments, a method for information and process modelling was developed in a previous work. The approach was also implemented prototypically as an expert system but has not been validated, yet. This work therefore presents the validation as an integral part of the overall evaluation of the automated security risk assessment concept. For a systematic validation, a reference security risk assessment is manually defined as a set of data for the comparison with the results of the automated expert system. In addition, the two main hypotheses with regard to the result quality and the process automation evaluated.

With the advent of mmWave communication in next-generation wireless networks and their associated non-line-of-sight coverage constraints, Integrated Access and Backhaul (IAB) technology has become increasingly relevant. Current IAB approaches assume fixed power connections, while the next step towards total mobility involves battery-operated IAB nodes. The potential scalability benefits of nomadic 5G+ networks with fully wireless nodes can be particularly valuable in dynamic application scenarios, offering the required adaptability while satisfying stringent network utility constraints. However, managing the balance between operational costs, pertaining energy efficiency, as well as communication integrity in IAB networks is a significant challenge and an active research topic. Consequently, this work in progress paper explores recent advances in IAB network management that aim to enhance energy efficiency and network utility. It identifies new research opportunities and discusses their challenges. Additionally, a conceptual Zero-Touch Management (ZTM) framework for optimizing the operational efficiency of IAB networks is proposed. The framework considers dynamic link scheduling and resource allocation strategies for improving energy usage. This ongoing study intends to provide preliminary insights into the current state of research on IAB network management, emphasizing the topics of energy efficiency and service quality as future research directions.

The overall Industry 4.0 developments and the highly dynamic threat landscape enhance the need for continuous security engineering of industrial components, modules, and systems. Security risk assessments play a major role to ensure a secure operation of Industrial Automation and Control Systems (IACSs) but are mostly neglected due to missing resources and a lack of human experts for the sophisticated manual tasks. Therefore, a method for information and process modelling regarding the automation of security risk assessments has been previously designed, but not yet evaluated. This work in progress begins the evaluation of the automated security risk assessment concept by investigating the related work and identifying the main deficits. The results include a requirements analysis for the verification and an outlook towards future evaluation aspects.

Due to Industry 4.0 developments, the demanded modularity of manufacturing systems generates additional manual efforts for security experts to guarantee a secure operation. The rising utilization of information and the frequent changes of systems necessitate continuous security engineering. Therefore, this work in progress presents the specification and prototypical implementation for automated security risk assessments. In addition, an outlook towards the associated validation, verification, evaluation, and hypothesis testing is given.

Current industrial communication systems (ICS) are undergoing a transformation, leveraging a multitude of technologies to meet the specific needs of the manufacturing and automation industries. The convergence of these networks into edge, fog, and cloud architectures has enhanced their scalability and facilitated the deployment of advanced data-driven approaches, such as machine learning for optimizing production processes. However, ensuring proper provisioning of network and computation resources, along with delivering quality of service, is increasingly challenging in these complex communication systems. Zero-Touch Management (ZTM) frameworks promise to reduce complexity and minimize dependence on manual configuration by human experts. Successful deployment of such frameworks requires an accurate Network Digital Twin (NDT) of relevant network elements, as autonomous decision-making heavily relies on the quantity and quality of historical and real-time node and link state information provided by the NDT. However, the use of NDTs for ICS and ZTM in particular is still an emerging research topic. This paper therefore proposes a theoretical use-case for an NDT-based ZTM framework to improve resource utilization in cloud-centered networks. It presents a state-of-the-art analysis of recent NDT advances enabling the deployment of related ZTM approaches and discusses associated challenges and future research directions.

Standardization and prototyping of Ethernet Time Sensitive Networking (TSN) makes progress and its mechanisms are utilized with various application protocols and technologies within the industrial automation domain. Sharing Ethernet TSN mechanisms in multi-protocol networks impacts interoperability. Although the International Electrotechnical Commission (IEC) and the Institute of Electrical and Electronics Engineers (IEEE) attempt to unify Ethernet TSN utilization with the IEC/IEEE 60802 TSN Profile for Industrial Automation, Ethernet TSN devices already exists on the market by different vendors. An area of conflict is the egress configuration of a single Ethernet-Interface for TSN streams of different technologies, such as PROFINET, CC-Link IE TSN and OPC UA Field eXchange. A practical post processing solution can be to merge Ethernet TSN configurations for a single port. A concept for a Configuration Merge Algorithm (COMEA) is presented in this work. A test environment consisting of multiple industrial automation applications with an Ethernet TSN network infrastructure is used to demonstrate the result of application.

Due to Industry 4.0 developments, the demanded modularity of manufacturing systems generates additional manual efforts for security experts to guarantee a secure operation. The rising utilization of information and the frequent changes of system structures necessitate a continuous and automated security engineering, especially by application of the mandatory security risk assessments. Collecting the required information for these assessments and formalising expert knowledge shall improve the security of modular manufacturing systems in the future. In order to automate the security risk assessment process, this work proposes a method to determine the Target Security Level (SL-T) in conformance to the IEC 62443 standard based on the MITRE ATT&CK framework and the Intel Threat Agent Library (TAL).

Smart cities will be significantly shaped by their modes of mobility. For the blend of public and individual transport, smart mobility will introduce autonomous vehicles on a large scale, which often heavily rely on communication. As the capabilities of autonomous vehicles are still limited nowadays, driver-less vehicles have to be able to be remotely monitored and controlled in real-time. This creates high performance demands for the vehicle’s communication link, especially regarding latency and uplink, which can easily exceed the limits of communication standards like Long Term Evolution (LTE). Therefore, the development of the communication system for the newly developed autonomous monorail vehicle MONOCAB aims towards the use of the 5G standard. This paper presents experiences and measurements from a first outdoor field test conducted in the context of monitoring and remotely controlling the MONOCAB via 5G. Previously, all communication services were subjected to ITU-T Y.1564 compliant tests for the network planning and the deployment of a 5G Non-Public Network (NPN). This deployed 5G NPN was then used to test remote monitoring the MONOCAB, at it’s first public presentation on the 3rd of October 2022, by transmitting video streams and telemetry data from the vehicle to a central control station. Additionally, a glass-to-glass latency measurement of a video stream transmitted via 5G was conducted, to point out the latency impact of 5G.

Increasing traffic congestion leads to significant costs, whereby poorly configured signaled intersections are a common bottleneck and root cause. Traditional traffic signal control (TSC) systems employ rule-based or heuristic methods to decide signal timings, while adaptive TSC solutions utilize a traffic-actuated control logic to increase their adaptability to real-time traffic changes. However, such systems are expensive to deploy and are often not flexible enough to adequately adapt to the volatility of today’s traffic dynamics. More recently, this problem became a frontier topic in the domain of deep reinforcement learning (DRL) and enabled the development of multi-agent DRL approaches that can operate in environments with several agents present, such as traffic systems with multiple signaled intersections. However, many of these proposed approaches were validated using artificial traffic grids. This paper presents a case study, where real-world traffic data from the town of Lemgo in Germany is used to create a realistic road model within VISSIM. A multi-agent DRL setup, comprising multiple independent deep Q-networks, is applied to the simulated traffic network. Traditional rule-based signal controls, modeled in LISA+ and currently employed in the real world at the studied intersections, are integrated into the traffic model and serve as a performance baseline. The performance evaluation indicates a significant reduction of traffic congestion when using the RL-based signal control policy over the conventional TSC approach with LISA+. Consequently, this paper reinforces the applicability of RL concepts in the domain of TSC engineering by employing a highly realistic traffic model.

The internet of things (IoT) requires an efficient management of all devices. Operation in potentially insecure environments, limited processing capability of the IoT devices and unreliable connectivity create the need of suitable Device Management (DM) solutions. But with the IoT being complex and diverse, the criteria for finding the right DM solution differ depending on the application-specific requirements of the given IoT system. In this paper, we develop a rating system for IoT DM solutions, which can be easily adapted. The criteria are represented with the FCAPS and the life cycle management models. Additionally, we conduct an evaluation of open source IoT platforms in contrast to commercial solutions.

The current static risk assessment processes and concepts do not match the increasing requirements with regard to flexibility within the industrial automation domain. The amount of manual tasks and needed efforts for risk assessments are too high in order to adequately cover the rising rate of system reconfigurations. Analysing the typical risk assessment processes from the IEC 62443 will show resource constraints with regard to time, bottlenecks, and the main cost drivers. If the most rewarding process steps can be identified and automated, the overall performance of risk assessments can be enhanced to keep up with the demanded flexibility.

Over the past decades industrial communication networks have evolved into highly diverse and heterogeneous environments, with a variety of different technologies being deployed to address the diverse requirements of manufacturing-and automation-specific use cases. These include stringent latency limits, high availability and reliability, as well as deterministic communication behavior. To assure the necessary allocation of re-sources and provisioning of required Quality-of-Service in highly diverse communication systems, a holistic network management approach is needed that can serve all cornerstones of modern industrial networks. More recently, this lead to the development of new adaptive and agile management approaches that imple-ment autonomous and self-organizing manufacturing networks, whereby Machine Learning (ML) methods started to become an integral part for overcoming the limiting factors of practically deploying such systems. Due to the growing complexity of today's networking environments, defining network management policies based on expert knowledge becomes increasingly difficult. ML has evolved as a promising technique to extract knowledge from collected data to enable cognitive network management approaches. This paper reviews past advances in ML applications for zero touch management of heterogeneous industrial communication networks. It illustrates how a network's management life-cycle that is based on digital twin technology can harnesses the potentials of ML to bring the concepts of organic computing and zero-touch cognitive manufacturing within industrial networks closer to reality. Lastly, recent papers that discuss the use of ML approaches for self-x features in Zero-Touch Management (ZTM) network environments are surveyed and relevant open issues are discussed.

The manufacturing domain is exposed to a continu-ous change of the requirements towards the IT infrastructure and the flexibility in Industry 4.0. In order to achieve a highly reliable production system, predictive maintenance and additive sensing have been implemented and will be complemented by further applications such as Augmented Reality. As the applications may be required ad-hoc at any time, the dynamic resource utilization of networking and computational resources needs to be managed. In the long-term, the planning of the infrastructure affects the available resources and thus the efficiency and reliability of the short-term resource management. This paper suggests an architecture that combines short- and long-term aspects of the resource utilization and previews how the infrastructure and opportunity costs can be optimized by the joint approach.

The automation industry discusses the deployment of processing resources in applications since decades. The two major subjects of discussion are centralized and decentralized computing. The deployment of artificial intelligence (AI) applications and the processing power is facing the same issue nowadays. AI is used in many different areas like smart city, industrial automation for pattern recognition or as an expert system and so on. However, it remains a central question how to deploy the AI within an application and how to connect the AI to other devices, services and agents. In this paper we discuss state-of-the-art architecture to structure general IoT applications, as well as, the two most common processing concepts. Furthermore, use cases in urban mobility and industrial automation to deploy AI applications are presented and an In-depth view to the implementation is discussed. Pros, cons and problems of the implementations are shown, which can provide ideas and references when deploying an AI application.

Sub-optimal control policies in intersection traffic signal controllers (TSC) contribute to congestion and lead to negative effects on human health and the environment. Reinforcement learning (RL) for traffic signal control is a promising approach to design better control policies and has attracted considerable research interest in recent years. However, most work done in this area used simplified simulation environments of traffic scenarios to train RL-based TSC. To deploy RL in real-world traffic systems, the gap between simplified simulation environments and real-world applications has to be closed. Therefore, we propose LemgoRL, a benchmark tool to train RL agents as TSC in a realistic simulation environment of Lemgo, a medium-sized town in Germany. In addition to the realistic simulation model, LemgoRL encompasses a traffic signal logic unit that ensures compliance with all regulatory and safety requirements. LemgoRL offers the same interface as the well-known OpenAI gym toolkit to enable easy deployment in existing research work. To demonstrate the functionality and applicability of LemgoRL, we train a state-of-the-art Deep RL algorithm on a CPU cluster utilizing a framework for distributed and parallel RL and compare its performance with other methods. Our benchmark tool drives the development of RL algorithms towards real-world applications.

The data driven services in industrial automation systems are transforming the world of automation industry by optimizing industrial processes and providing Value Added Services (VASs) with the grace of Industry 4.0, Big Data and Artificial Intelligence (AI). A demand driven data pipeline is essential to connect different industrial data sources in a shop floor with different data storage systems for service provisioning. This paper analyzes an experimental approach and corresponding challenges to optimize computing resource allocation in industrial applications to construct such demand driven data pipeline to provide data driven services through an open source, flexible and extensible distributed query engine known as Presto, which can perform interactive analytical queries for different purposes such as condition monitoring, asset management or many others.

Increasing customization and dynamically allocated services for data analytics and production optimisation are forcing the industrial networks of the future to become more flexible and adaptive. Moreover, future converged networks require a higher degree of scalability and performance. Three technologies are currently under special observation for solving this issue: Time-Sensitive Networking, Software-defined Networking and OPC UA. This paper combines these three technologies into one network architecture. This architecture shows that it is possible to configure time-sensitive traffic streams by leveraging the Time-Sensitive Networking methods for synchronisation and Time Aware Shaping in combination with forwarding methods coming from Software-defined Networking. OPC UA is utilized as the link for industrial applications to interact with the network management and transmit their demands on the network service. Additionally, OPC UA serves as the data exchange technology among industrial applications by utilizing OPC UA PubSub and leveraging Quality-of-Service queues according Time-Sensitive Networking standards. It can be shown that the combination is a reasonable solution and a promising field for further investigation.

The advances in industrial automation systems rise more stringent demands for reliable and flexible communication. 5G and TSN have been discussed widely as promising candidates that fulfil these requirements. To take advantage of the combination of both of these technologies, an integration of 5G with TSN is part of the current work on the 5G specifications. In this paper, a simulation approach for OMNeT++ based on the existing TSN model NeSTiNg and a novel lightweight 5G user plane model that is still under development is presented. By means of a relevant closed loop control simulation, the known issue of different scheduling periods is reproduced in a minimal simulation scenario. Furthermore, crucial further steps to optimize the model towards an IEEE 802.1Qbv TSN bridge are identified as future tasks.

Real-time behaviour is one of the most important aspects of field level automation networks in factory communication. Various Real-Time Ethernet (RTE) technologies have been developed over the years to cope with the network requirements like latency, Quality-of-Service (QoS), reliability etc. of the field level networks. Because of their nature of vendor-dependency, these technologies have been incompatible with one another. In the era of Industry 4.0, an innovative approach is required to bring together this technology in order to solve the interoperability issue. Open Platform Communication Unified Architecture (OPC UA) is a vendor-neutral communication protocol which can be an answer to this incompatibility problem of field level factory networks. This paper aims to use OPC UA as a field level communication protocol in combination with the Time-sensitive networking (TSN) standards to simulate the real-time behaviour of field network.

Optimally scheduling jobs in processing networks to meet multiple objectives for economic considerations and operational efficiencies has been a hot topic. However, most data-driven methods are rarely applied. One of the critical reasons is that the scheduling policy generated by these methods tends to bias toward the specific environment. In order to better deal with the discrepancy, this work in progress paper presents a context-aware dynamic scheduling method (CADS) that can adaptively select a specific policy based on the on-demand context. The CADS has two components: 1) The evaluation module that evaluates the performances of the policies that are learned from each operational context; 2) The decision-making module that maintains the knowledge of each policy’s performance under each context and constructs the weighted best-fit policy based on the identified context. The promising preliminary result using numerical simulation that demonstrates the effectiveness of CADS is presented. CADS outperforms traditional scheduling methods in various kinds of processing network environments.

Increasing heterogeneity of industrial network systems is a fact and the chances that in the future one communication standard will be able to fulfill the requirements of all possible applications are utopian. With the increasing number of communication systems, their management, configuration, and maintenance become a significant issue. Additionally, due to the increasing amount of network services and traffic, the management of available network resources and the possibility of delivering certain levels of communication quality of service, especially across different network solutions becomes a big challenge. Therefore, in this paper a Controller of Controllers (CoC) concept for management of heterogeneous industrial networks is proposed. The concept is designed to support still widely spread legacy fieldbus systems, different Ethernetbased industrial solutions, and potentially upcoming network technologies. The goal is achieved by leveraging state-of-theart architectural concepts such as software-defined networks, which allows for integration of abstract models in network management. The concept is described and discussed by way of a demonstrator concept for a heterogeneous system of fieldbus and Ethernet-based time-sensitive networks.

The advent of Industry 4.0 brings the Internet of Things (IoT) and Cyber-Physical Systems (CPSs) inside the factory premise and made the boundaries between the information and operational technologies (IT & OT) obsolete. This, in turn, introduces the problem of interoperability due to the integration of multiple industrial protocols and technologies from various automation networks. The aim of this paper is to investigate this interoperability problem of heterogeneous network management and propose a semantic network knowledge base as a solution to it. It also describes a set of generic interface functions for data acquisition.

Driven by rapid digitalisation, production systems are becoming more flexible and adaptable with the help of emerging concepts like the Internet of Things (IoT) and Industry 4.0. Often, these transformations are not fully implemented in Small and Medium-sized Enterprises (SMEs) due to the replacement cost of existing machines. This paper aims to develop a Plug & Play retrofitting platform, where Industry 4.0 compliant sensor systems can be attached, detected, and configured automatically to the existing production environment. The purpose of the retrofitting is to integrate the sensor system with a cloud platform that would provide persistent storage for sensor data as well as the functionalities to perform monitoring, analysis, and predictive learning.

Future industrial production systems following the paradigms of Industrie 4.0 will be reconfigured frequently and new system configurations will be deployed automatically as part of the engineering processes. In order to keep pace with this requirement of increased flexibility, it will be needed to achieve the adequate security levels in an automated way and to reduce the current static procedures and manual efforts as much as possible. Therefore, a modelling of all security-related functionalities and capabilities is mandatory. This paper further describes an approach for such a modelling based on the IEC 62443 security standard and an implementation of an automated deployment of components inside an industrial environment established with the OASIS Tosca and Ansible tools. The first results of the whole tool chain are evaluated with a real-world use case of software deployment in a suitable lab environment.

The prevalence of the term “Network Slicing” in today's communication network research community signifies the concept worthy of focus. However, despite its ubiquitous usage, there are varied interpretations of the concept which often leads to disagreement and confusion. The root of this misunderstanding lies in what the term “Slicing” means to the user and the context of its application. Network slicing has been considered as a key concept in 5G which will enable various types of services like enhanced Mobile Broadband (eMBB), Ultra Low Latency Reliable Communication (URLLC) and massive Machine Type Communication (mMTC) for industries. Despite all the standardization efforts, less progress has happened in the field to demystify the concept due to the misinterpretation of the term by various parties. As a result, this paper aims to provide an industrial perspective on the concept of Slicing and its usage in industrial communication networks. It shall as well propose contextualized taxonomy of the areas of usage as a way of reducing the vagueness surrounding the concept. Thus, within this context, an objective rather than subjective comprehension can ensue in intellectual discussions.

The upcoming fifth generation of mobile networks (5G) is supposed to enable innovation in industries like factory and process automation by addressing machine-type communication and its requirements of reliability and latency. However, 5G will not immediately fulfill all the requirements raising from industrial applications at reasonable costs. The integration of 5G as a network entity into an industrial communication system is therefore considered as an applicable migration path. In this paper, a flexible and adaptive integration of a 5G mobile network into the industrial Ethernet protocol Profinet utilizing the network slicing concept will be proposed.

In the environment of modern processing systems, one topic of great interest is how to optimally schedule (i.e., allocate) jobs with different requirements for the systems to meet various objectives. Methods using distributed reinforcement learning (DRL) have recently achieved great success with large-scale dynamic scheduling problems. However, most DRL methods require a huge amount of computational time and a large amount of data for the DRL agents for a control policy. Meanwhile, various scheduling experts have already developed several scheduling policies (i.e., dispatching rules) that can successfully fulfill different objectives with acceptable performance for a processing system based on their understandings of the processing systems characteristics. In this paper, we propose to learn from experts to reduce the learning and searching costs of a good policy in large-scale dynamic scheduling problems. In the learning process, our DRL agents select the experts who have better performance in the scheduling environment, observe the experts' actions, and learn a scheduling policy guided by these experts' demonstrations. Our realistic simulations results demonstrate that this expert-guided DRL (EGDRL) approach outperforms DRL methods without expert guidance, as well as some other reinforcement learning from demonstration (RLfD) methods in several systems. To the best of our knowledge, our research is one of the first works that incorporates existing expert policies to guide the learning of optimal policies for large-scale dynamic scheduling problems.

Due to the dynamic nature of the Industrie 4.0 developments, future production systems will be reconfigured more frequently and new system configurations will be deployed automatically. In order to keep pace with this development, it will be required to observe and ensure the needed security functionalities and corresponding certifications in an automated way. This implies an improvement of today's static procedures and manual efforts as much as possible in favor of a dynamic standard establishment. Therefore, this paper evaluates the state of the art of the industrial security standardization landscape and proposes a concept for the automated support of certification processes with information from industrial communication networks in order to enhance the usability of the standards establishments and the certifications within organizations and companies, especially small and medium-sized enterprises.

Maintenance is an important set of various activities related to preserving from failure or decline. Improper or lack of maintenance may result in excessive component wear, production quality deterioration, or even longer downtime. However, today's production facilities strive to devote the least amount of necessary maintenance time in order to maximize production time. Therefore, new solutions for deliberate and efficient maintenance are needed. The solution proposed in this paper benefits from the newest trends and innovations in industry, namely the Asset Administration Shell (AAS) which is part of the Industrie 4.0 (I4.0) concept. The AAS shall contain the maintenance submodel which shall be used for supporting humans during the maintenance process. The submodel provides a standardized description of required tools and parts as well as step-by-step instructions which also include safety concerns and multimedia files, such as pictures and videos. In this way, maintenance can be carried out more reliably, resulting in reduced downtime. In addition, feedback from the maintenance process shall be stored in the submodel and fed through an I4.0-compliant network to other processes from different phases of the life cycle in order to improve them.

The overall Industry 4.0 (I4.0) developments combined with the disruptive process of IT-based digitalisation create a vast amount of new opportunities but also challenges for the industrial automation domain. The combination of hybrid (wired & wireless) communication architectures, already widely installed legacy technologies, new approaches, such as Time-Sensitive Networking (TSN) or 5G, and the general heterogeneity of the industrial landscape results in a high configuration complexity. This creates the necessity for future-proof industrial communication network management systems. Therefore, this paper summarises the current state of the art in this area in order to identify the specific requirements towards future industrial network management systems. The most promising candidate is the Software-Defined Networking (SDN) concept. To evaluate SDN as a possible enabler, specified industrial requirements are compared with the current technological and conceptual capabilities of SDN. In addition, drawbacks resulting in future research questions are identified.

The Smart Factory Web (SFW) is a platform that connects Smart Factories over a network to enable flexible sharing and management of resources, assets and inventory to maximize production and efficiency. In order to become part of the Smart Factory Web, network participants describe not only their products, but also the factory capabilities to order to improve factory-to-factory collaboration. A Smart Factory Web Portal (SFWP) enables secure data and service integration in cross-site application scenarios as well as `plug & work' functions for devices, machines, and data analytics software by applying industrial standards, Open Platform Communications Unified Architecture (OPC UA), and Automation Markup Language (AutomationML or AML for short). OPC UA serves as a comprehensive and secure communication protocol from the machine level into the cloud. A Cloud Coupler on the shop floor publishes the availability of a factory and selected process data in the SFWP. Customers or even smart machines can use this information to make decisions for placing an order and track their orders in real time. In order to simplify the setup of the connection to the cloud and minimize the commissioning time the cloud coupler also aggregates all OPC UA servers on devices in the factory into a single OPC UA aggregated server address space. In this paper an architecture is proposed which uses cloud coupler and plug and work techniques to make a new or retrofit factory available in a SFW to share capability information towards a new marketplace for manufacturing. It is shown that the integration efforts are decreased but also the use of standards reduces the effort to define interfaces.

The dissolving of the automation pyramid in the course of the fourth industrial revolution will impact the design of industrial networks. Especially processing components which nowadays are residing on a machine can be potentially located remotely in the factory IT or even beyond. In order to fulfill the still existing requirements of industrial automation processes, the network especially the infrastructure devices like switches and routers must be enhanced by new technologies granting real-time capability. Furthermore, the network has to meet Industry 4.0 demands regarding security as well as more flexibility like auto-configuration or seamless reconfiguration. A solution concept to establish secure and time-sensitive communication for remote process control and monitoring as well as first implementation steps are proposed. The concept and implementation include current technologies like Time-Sensitive Networking and deterministic networking in combination with Software-defined Networking. This grants flexibility regarding the configuration of time-sensitive industrial networks and adds possibilities to secure them.

In the area of demand-driven manufacturing systems, one critical problem currently is how to dynamically and optimally schedule, i.e., allocate, actual jobs with different customer requirements in large-scale manufacturing systems in order to meet the various objectives. Scheduling experts have proposed several scheduling methods with acceptable performance for manufacturing systems based on their understanding of the systems' characteristics. However, the problem remains challenging due to the complicated composition of the multiple objectives of the system, the complex system dynamics, constraints, and the extremely high computational cost for large-scale manufacturing systems. In this paper, we apply a stochastic processing network that can capture the stochasticity and dynamics of discrete manufacturing systems. We then propose a data-driven, distributed reinforcement learning (DRL) method so that little information about the system dynamics is required, and the learning and search costs of a scheduling policy with high production performance in a processing system can be reduced, thus this method is capable of scaling to large-scale processing systems. In particular, we first use a stochastic processing network, i.e., a queueing model, to represent the production processes in a typical discrete manufacturing system so that it can be simulated. We then decompose the reinforcement learning into local processes. Each local processs agent can make decisions locally by assigning indices to jobs based on each job's real-time information (index policy). Because of this distributed learning characteristic and index policy, our approach is much more scalable and efficient than either centralized methods or traditional decentralized reinforcement learning methods. Based on our simulation, we find our approach can achieve higher production performance than other heuristics, past decentralized reinforcement learning methods, or centralized methods in the stochastic processing networks with different scales.

The fourth Industrial Revolution is finding its way into modern manufacturing sites. Assets with a certain degree of implemented communication technology will be enabled to interconnect and cooperate with practically every other entity via the Industrial Internet. An extreme amount of data and information will be exchanged all the time. Machines will be empowered to make crucial decisions autonomously influencing whole production processes. Erroneous, illegitimate or tampered data will lead to incorrect decisions and will be posing a huge threat to future strong cross-linked added value networks. An approach to tackle this issue comes from a technology called distributed ledger technology with its most known variant the “blockchain”. Certain properties of blockchain technology are showing promising enhancements for industrial networks primarily in order to guarantee digital trust. In this paper, issues like the ability to scale and the adaption onto the requirements of industrial networks are investigated. It turns out that simulation approaches must be taken into consideration, and a first step for an implementation is presented.

The Plug-and-Produce concept requires that after connecting a new module to a system, the exchange of the configuration data takes place. As further operation of the system depends on this initialization procedure, it is necessary to ensure that the data presented by the system and the newly attached component is authentic. Therefore, we propose a new concept for secure Plug-and-Produce functionality, which exploits the combination of the Asset Administration Shell (AAS) and Blockchain technology. On the one hand, the AAS shall be responsible for presenting uniform and standardized configuration data as well as for storing and managing Blockchain. On the other, Blockchain shall ensure authenticity and integrity of the configuration data.

The process of digitalisation has an advanced impact on social lives, state affairs, and the industrial automation domain. Ubiquitous networks and the increased requirements in terms of Quality of Service (QoS) create the demand for future-proof network management. Therefore, new technological approaches, such as Software-Defined Networks (SDN) or the 5G Network Slicing concept, are considered. However, the important topic of cyber security has mainly been ignored in the past. Recently, this topic has gained a lot of attention due to frequently reported security related incidents, such as industrial espionage, or production system manipulations. Hence, this work proposes a concept for adding cyber security requirements to future network management paradigms. For this purpose, various security related standards and guidelines are available. However, these approaches are mainly static, require a high amount of manual efforts by experts, and need to be performed in a steady manner. Therefore, the proposed solution contains a dynamic, machine-readable, automatic, continuous, and future-proof approach to model and describe cyber security QoS requirements for the next generation network management.

In Germany, as of 2017, a new smart metering infrastructure based on high security and privacy requirements will be deployed. It provides interfaces to connect meters for different commodities, to allow end users to retrieve the collected measurement data, to connect to the metering operators, and to connect Controllable Local Systems (CLSs) that establish a TLS secured connection to third parties in order to exchange data or for remote controlling of energy devices. This paper aims to connect industrial machines as CLS devices since it shows that the demands and main ideas of remotely controlled devices in the Smart Grid context and Industrial Cloud Applications match on the communication level. It describes the general architecture of the Smart Metering infrastructure in Germany, introduces the defined roles, depicts the configuration process on the different organizational levels, demonstrates the connection establishment and the initiating partners, concludes on the potential industrial use cases of this infrastructure, and provides open questions and room for further research.

For cyber-physical systems (CPSs), communications system reliability is an indispensable requirement to realize them in critical infrastructures. One of the important attributes of system reliability is availability. System availability is broadly defined as the proportion of time that the system will provide service. In some CPSs, such as smart grids, the units are distributed over large geographical areas. For such systems, the use of Internet to connect their units is highly desirable. However, the reliability of today's Internet was considered to be inadequate to support many CPSs. In this paper, we propose the utilization of multipath (MP) communications using different end-to-end (e2e) paths to improve communications reliability of Internet for CPSs. With this regard, we first formulate the problem of multipath selection to provide the required communications reliability as an optimization problem. After that, we conduct first real world measurements to investigate the diversity of different e2e paths and the reduction in communications service unavailability when 2 and 3 paths between the source and destination are considered simultaneously. Our results indicate the existence of e2e paths that traverse completely different networks and, consequently, are likely to be disjoint. In addition, the concurrent unavailability of different 2 and 3 paths combinations was 0. The results show that MP communications using different e2e Internet paths can achieve the required reliability by many CPSs such as smart grids.

The exhaustive digitalization of the economy, and to be more specific, of industrial production systems results in a new quality of information transparency. This is the basis for added values in terms of effectiveness, quality, and individuality. However, these added values also result in an increased exposure to Cyber-Security threats, due to the increased digitalization, information transparency and standardization. In this work, the procedural model for a Cyber-Security analysis based on reference architecture model Industry 4.0 (RAMI 4.0) and the VDI/VDE guideline 2182 is exemplary shown for the use case of a Cloud-based monitoring of the production. The derived procedure supports the identification of protection demands and allows a risk-based selection of suitable countermeasures.

Currently, cloud computing offers flexible, dynamic and cost effective computing outsourcing, but it limits these economic and operational benefits to non real-time and non safety-critical systems. This is because of the lack of alternative control, supported by current cloud infrastructures, in case of a broken cloud link. While steps have been taken in using cloud infrastructures for soft real-time systems in industrial operations, such as using a virtualised PLC from a cloud, a gap still exists in appropriate handling of operations in the case of a broken cloud link. This paper proposes a new hybrid approach for providing control services from the cloud that can handle the essential communication locally in case of a broken cloud link. The proposed approach is also tested with two different scenarios for an initial evaluation.

Recent developments under the term Smart Grid change how users consume electricity and interact with the power grid. Smart metering and energy management are developments that transform the yet passive energy consumer to a participant that is actively involved in the energy market by using variable energy tariffs or by demand-response services. But such functionality demands a platform that integrates all smart devices in the users property, connects to external services and electricity providers, and has interfaces that provide information and control to the user. AnyPLACE will develop such platform. Based on the latest legislation in the European member states, it will incorporate smart meters and create links to external service providers. Furthermore, it connects the devices in the property of the end-user in order to be able to fully monitor and control the energy consumption. This paper presents the AnyPLACE idea and the problems that are solved on the communications aspect. It provides an in-depth analysis of current European legislation in the context of smart metering and provides the requirements that need to be realized by the platform. Additionally, it proposes a strategy to create a solution that can be used in any place of Europe. The paper also incorporates the security and privacy requirements in different domains and sketches a solution and architecture to fulfill these by incorporating existing open source implementations as provided by the openHAB project.

Software-Defined Networking (SDN) is a promising approach to build future industrial networks. The disruptive change of network architecture and management opens new possibilities in various application domains. While the approach is already deployed in several domains and was also initially examined to be used in the industrial area, many open questions arise when assessing the risks and improvements to be expected. The following work presents features of a potential future industrial network infrastructure and sets up requirements that are important for future communications. It reviews basics of SDN and correlates existing work to the specified requirements. Finally, it presents open questions and room for future research.

Scheduling of time triggered communication systems belongs to the well known hard mathematical optimization problems. This paper tackles the communication scheduling problem in redundant network topologies, where the real-time process data has to be duplicated and sent on two different paths to its destination. This paper proposes an algorithm that is able to find a feasible schedule in a short time, while keeping the makespan of the schedule in average 10% shorter than the makespan of the schedule produced by a commercial tool, which is the current benchmark.

In the industrial automation a paradigm shift from centralized, static automation structures to reconfigurable manufacturing systems (RMS) might be lie ahead. RMS are seen as a key enabler for the required changeability of future production companies since they can reduce the engineering effort needed for the reconfiguration of existing or the construction of new production systems. However, it is not clear how the companies can benefit from RMS in detail. For example, the reduction of engineering effort cannot be expressed in figures by today. But such information is necessary to convince the industry of the advantages of the new production principle. Indeed, existing RMS paradigms like Service-Oriented Architectures are rarely used in the practice of automation. The basis for analyzing the advantages of RMS is an analysis of the status quo in the industrial automation. Regarding the engineering effort of current automation systems, this paper will present a case study considering the effort occurring during the commissioning process of a production system constructed by state-of-the-art components. The evaluation of the study can serve as a reference when comparing the engineering effort of RMS with today's systems.

The term Industrie 4.0 carries the vision of smart factories, which automatically adapt to changes and assist the human as much as possible during operation and maintenance. This includes smart human machine interfaces, which reduce the chances of errors and help to make the right decisions. This paper presents an approach to equip the maintenance software running on a tablet PC with augmented reality functionality to be able to place virtual sticky notes at production modules. Additionally, these sticky notes are enriched with position information. The central element of this approach is an ontology-based context-aware framework, which aggregates and processes data from different sources. As a result, a tablet PC application was implemented, which allows displaying maintenance information as well as live plant process data in the form of augmented reality. More than 100 of those sticky notes can be placed using this system, whereas each note requires a file size of 12 to 16 kilo bytes. After placing a sticky note, the system recognizes it even if the camera's position is not exactly the same as during the placing process.

Cyber-Physical Systems (CPSs) represent a new paradigm of future intelligent systems. They consist of loosely coupled subsystems which interact with mechanisms of Service-oriented Architecture (SoA). In this paper we try to open a new topic in industrial communications. This topic is focused on basic communication patterns within CPSs. Patterns are abstract and generic solutions for common problems in the design of systems. They have a defined feature set, their flaws are known, and they help to avoid repeating errors. Furthermore, patterns introduce a common vocabulary within a community, which simplifies communication between people and documentation. Patterns often represent best practices that are used in already existing protocols. Therefore this work starts to evaluate different existing communication protocols in the scope of SoA and loosely coupled systems, extracts common tasks and implementations, and identifies common communication patterns.

In this paper, an FPGA based FIFO with efficient memory management is proposed, which allows fast forwarding of real-time Ethernet frames. There are two main drawbacks of the existing FIFO implementations with respect to the buffering of Ethernet frames. Currentness of data is not guaranteed in case of buffer overflow because the new frames are dropped in this case. Furthermore, exhaustive resources are required for traffic priorization because an individual FIFO is required for each priority level. The proposed FIFO incorporates efficient strategies for both frame dropping and traffic priorization. The approach is based on a small ring buffer for meta data of individual frames and a page table that maps the frames to pages in RAM where the data bits of the frame are stored. The FIFO has been implemented on a low-cost Xilinx Spartan 6 FPGA. The solution requires little overhead for page table and ring buffer. Compared to an implementation with standard FIFOs that incorporates traffic priorization and frame dropping, RAM size is decreased from 44 kbytes to 2.7 kbytes.

Many aspects have to be considered while achieving flexibility of production systems. One of them is flexible communication system that on one hand fulfils requirements of a particular industrial application and on the other hand allows integration of new network components optimally in a seamless way. In this paper, an approach to increase, rather static, Time Triggered Ethernet based systems is proposed. It is based on a greedy scheduling approach that can be implemented directly in a processing limited hardware such as IO Controller. This, together with the discovery and auto configuration mechanism proposed in [1] allows to shift the engineering process typically performed offline using engineering tool to the field level. Furthermore, it has been proven that the proposed scheduling approach is not only simple but also powerful. It is able to calculate an optimal schedule for any kind of tree graph and the complexity of the algorithm is defined by the complexity of the used sorting algorithm.

Cyber-physical systems (CPSs) are a new paradigm of control systems where control, communication, and computation fields intersect. Applications of such systems are expected to play an important role in many domains in the future. This includes critical domains such as transportation and health domains. Hence, it is quite important for such systems to operate reliably. Moreover, many CPS applications are characterized by having different modes of operation along with different corresponding traffic patterns and communication requirements. All this requires reliable communication networks that provide not only quality of service (QoS) support but also flexibility to adapt according to the varying communication requirements of the application/user. On the other hand, recent cellular standards such as Long Term Evolution (LTE) offer higher QoS control compared to earlier cellular standards with the ability to differentiate traffic at both the service and user levels. In this paper, we evaluate the ability of LTE cellular technology under certain QoS and load conditions to provide reliable communications for CPS applications characterized by possessing different modes of operation along with different corresponding traffic patterns and communication requirements. Our evaluation results indicate the ability of LTE cellular technology to provide reliable and adaptable communications for CPSs when QoS is provided.

Future market conditions require production systems which can be easily adapted to changing demands. However, the engineering process of industrial automation systems is characterized by high manual configuration efforts. Thus, the reconfiguration of such system leads to time-intensive and expensive downtimes. Therefore, this paper will present a concept on reducing the engineering effort - at least on the lower layers of the automation pyramid. Due to the real-time requirements on these layers, specific communication technologies must be used there - for example Real-Time Ethernets (RTEs) which are increasingly applied in industrial automation. However, their real-time capability is contrasted by an additional configuration effort in comparison to standard networks from the information technology domain. This paper will show an approach for the automatic configuration of RTEs and will check its applicability on the most widely-used RTE variants.

Cyber-physical systems (CPSs) represent a new generation of control systems where distributed local control systems are connected not only physically, but also computationally by means of communication networks. CPSs target introducing intelligence beside traditional monitoring and control functionalities in a way that optimize the performance of the overall system. However, the realization of many CPS applications requires reliable communication systems that provide quality of service (QoS) control. In this domain, Long Term Evolution (LTE) standard offers a comprehensive QoS frame work. Nevertheless, commercial implementations of the standard provide only best effort type of service. In this paper, we demonstrated the benefits of using LTE networks with QoS support for CPSs by comparing the performance of a CPS application over LTE network with and without QoS support. The results clearly indicate the benefit to enable the QoS features in commercial implementations of LTE in order to realize reliable CPS applications.

One of the key aspects to consider increasing flexibility of production plants is the industrial communication system. In case of time triggered Ethernet (TTE) systems, the flexibility is typically limited. In this paper an approach for seamless reconfiguration of TTE system is proposed. It has been shown that the reconfiguration can be performed without influencing currently running system.

Today, automation suppliers need to provide a large variety of field devices because one device is especially designed to provide a limited and static range of functionalities, which are fixed at the delivery time of the device. This is expensive for both customers and device suppliers. To overcome this situation, device functionalities needs to be adapted or extended on demand according to the changing market requirements, even if the devices have already been delivered to customers. In this work, an app-based approach is proposed and evaluated to serve that purpose. This approach is adapted from the smart device industry and it is used to provide software-based functionalities for field devices as an enabling technology in the context of reconfigurable manufacturing systems. This paper describes the essential elements of such an approach with a practical perspective.

Within a manufacturing system, a smart human-machine interface reduces the chances of human error and helps users to make informed decisions, especially in critical situations. This paper presents a concept for a flexible context specific assistance system for industrial applications using camera based localization. As a central element, a modular and service oriented context aware system aggregates relevant data from different sources. An object recognition service applies image analysis techniques on a video stream, captured from a top mounted multi-camera system to detect a person's location and associate it with a mobile device. A semantically enriched OPC UA server provides access to process data, and a web-service provides connection to a user interface hosted on a tablet PC. A case study provides an application of the proposed solution for the maintenance support and indoor navigation is implemented as a proof of concept.

One of the most important requirements for the industrial networks, apart from the real-time capability, is the reliability. There are several methods that can be used to increase the communication reliability. One of them is data duplication, which is afterwards transmitted using two different (disjoint) paths. Since, such path search for time triggered Ethernet based systems is typically done during engineering, it is important to keep the time needed for that as short as possible. Especially, if some topology changes are foreseen causing system re-engineering. Therefore in this paper an algorithm is proposed that has linear time complexity and is able to find two possibly disjoint paths for an arbitrary network topology in a short time.

Cloud computing has recently emerged as a new computing paradigm in many application areas comprising office and enterprise systems. It offers various solutions to provide a dynamic and flexible infrastructure to host computing resources and deliver them as a service on-demand. Since industrial automation systems of the future have to be adaptable and agile, cloud computing can be considered as a promising solution for this area. However, the requirements of industrial automation systems differ significantly from the office and enterprise world. This paper provides an overview of the latest concepts of cloud computing technology for industrial automation. Existing works are categorized based on the levels of automation systems and research gaps are discussed based on these findings. A general cloud model for automation is derived from existing proposals by refining them further. This cloud model will offer automation functions as services from a dynamic infrastructure.

Because energy efficiency is gaining more importance these days and Bluetooth Low Energy (BLE) could be used to make use of potential everyday objects into Internet of Things (IOT) - a software, platform and vendor independent common service interface that can be used in such low resource devices has high potential. OPC UA is an emerging middleware solution that addresses the above points but is bulky due to its abundant features. Further optimization is necessary to bring the OPC UA into such resource-limited devices. We have scaled down the OPC UA protocol stack footprint down to the chip level [16]. In this paper, we propose an optimization approach to minimize the OPC UA network footprint.

Deploying wireless technologies in industrial automation becomes more and more common. It is an enabler for many innovative applications where moving system components are involved, e. g. rotating parts of machines. However, many of such applications impose high temporal requirements on the wireless system, for instance isochronous data communication. Today, these requirements can not be met by existing solutions, such as IEEE802.11 Wireless Local Area Networks (WLANs). In this paper, an isochronous wireless communication system is investigated. It mainly consists of a deterministic medium access control, based on IEEE 802.11, which is extended with additional features for isochronous communication. The presented preliminary analysis shows the system's feasibility for the targeted industrial applications and presents promising performance improvements in comparison with standard mechanisms.

Industrial automation systems become more and more open for vertical integration using standardized information technology from the office world and access to the field level via Internet (Internet of Things and Industry 4.0). To protect such open automation systems there is a growing demand for the availability of suitable security features. However, real-time communication protocols used in automation networks typically provide no security functionalities and automation networks are vulnerable to numerous threats. In order to protect open automation systems, at least the authenticity of transferred data should be ensured. Therefore, an analysis of algorithms suitable for authenticity protection of data transferred by real-time Ethernet communication systems is presented in this paper. This includes an analysis of these algorithms and measurement results for a typical embedded system used in industrial Ethernet devices.

In the future, production systems will consist of modular and flexible production components, being able to adapt to completely new manufacturing processes. This requirement arises from market turbulences caused by customer demands, i. e. highly customized goods in smaller production batches, or phenomenon like commercial crisis. In order to achieve adaptable production systems, one of the major challenges is to develop suitable autoconfiguration mechanisms for industrial automation systems. This paper presents a two-step architecture for the autoconfiguration of real-time Ethernet (RTE) systems. As a first step, an RTE-independent device discovery mechanism is introduced. Afterwards, it is shown how the parameters of an RTE can be configured automatically using Profinet IO as an exemplary RTE system. In contrast to the existing approaches, the proposed discovery mechanism is based on the OPC Unified Architecture (OPC-UA). In addition, a procedure to autoconfigure modular IO-Devices is introduced.

Many implementations of the OPC-UA are increasingly available. Until now, use of technologies like the OPC-UA was limited to embedded systems with a sufficient amount of memory resources. OPC-UA offers a scalable feature set that could be tailored according to application demands. We believe that a key to successfully enable Internet of Things for the industrial automation applications lies in bringing down the OPC-UA into low end resource-limited devices, such as sensors. Because the OPC-UA provides a powerful information representation that is exchangeable through interoperable services. This paper has investigated the OPC-UA as a middleware solution for such resource-limited devices. For a proof of concept we have implemented an OPC-UA server based on the “Nano Embedded Device Server profiles” of the OPC Foundation.

The thirteen papers in this special section focus on the deployment of distributed computer systems in industry.

Nowadays, computer systems are presented in almost all types of human activity and they support any kind of industry as well. Most of these systems are distributed where the communication between nodes is based on computer networks of any kind. Connectivity between system components is the key issue when designing distributed systems, especially systems of industrial informatics. The industrial area requires a wide range of computer communication means, particularly time-constrained and safety-enhancing ones. From fieldbus and industrial Ethernet technologies through wireless and internet-working solutions to standardization issues, there are many aspects of computer networks uses and many interesting research domains. Lots of them are quite sophisticated or even unique. The main goal of this paper is to present the survey of the latest trends in the communication domain of industrial distributed systems and to emphasize important questions as dependability, and standardization. Finally, the general assessment and estimation of the future development is provided. The presentation is based on the abstract description of dataflow within a system.

Nowadays the deployment and commissioning of complex production processes or Internet-enabled applications interacting with production systems requires a time consuming and error-prone manual system configuration process. This is due to the need to maintain a high level of determinism, safety, and security of the production process itself and avoiding both safety-critical failures and costly production interruptions. The project “IoT@Work - Internet of Things at Work” aims at delivering tools and runtime mechanisms to significantly simplify commissioning, operating, and maintaining complex production processes, thus enabling Plug-and-Produce for automation systems. This paper presents a novel approach for the autoconfiguration of real-time Ethernet systems, and all relevant mechanisms. A case study, based on Profinet IO, evaluates the approach and shows its feasibility.

This paper presents an approach for the enhancement of standard switch ASICs with real-time Ethernet functions. Whereas a standard switch ASIC provides sophisticated mechanisms for switching of non real-time frames, an attached FPGA implements cut-through switching of real-time frames. The proposed FPGA architecture supports configuration of port numbers, bandwidth reservation for real-time frames and utilizes flow-control mechanisms of the ASIC in order to keep frame buffer sizes low. Mapping exemplary RTE extensions of PROFINET IRT onto a Xilinx Spartan 6 FPGA demonstrates the capability of providing band-width reservation and cut-through-forwarding of real-time frames. Therefore, the approach benefits from the innovations made by the switch manufacturers, whereas only a small amount of functions has to be mapped onto an FPGA.

This paper investigates prospects of the emerging IEEE 802.1 Audio Video Bridging (AVB) Ethernet standard in industrial automation applications. The notion of a small and predictable latency is common for both industrial and multimedia (audio, video) applications. The inbuilt characteristics of 802.1 AVB that includes synchronization, real-time traffic scheduling & shaping and resource reservation makes it a real-time capable Ethernet solution, which can be used for the process control applications as well. This paper presents a way to integrate the industrial process data communication to the lower layer services of IEEE 802.1 AVB, and describes a demonstrator implemented for a proof of concept.

Model-driven system/protocol engineering has been successfully applied in the industrial automation domain over the recent years. However, its cousin model-based testing (MBT) is relatively a new kid in the block - who is being curiously observed by domain experts. MBT leverages behavior models (e.g. software models) to automatically generate a large set of test cases. Testing industrial communication and automation systems manually for all significant behavioral scenarios is a non-trivial task. Hence, automatic generation of test vectors from formal/semi-formal models is desirable. Here, we report our first step towards the usage of MBT in the industrial automation context.

Wireless technologies are increasingly deployed in factory automation systems. They enable completely new application scenarios. Especially, IEEE 802.11 systems are of a high interest, due to their similarities to existing realtime Ethernet networks. However, existing implementations are only offering prioritization of frames and are lacking to meet certain real-time constraints when additional best-effort traffic is present. Therefore, an implementation of an isochronous medium access control is presented in this paper which is able to provide real-time guarantees based on time division multiple access. The hardware and software architecture is introduced and a first preliminary evaluation of the implementation shows its performance in terms of temporal behaviour.

Production facilities have to cope with fast changing market demands-leading to a need for high adaptability of the manufacturing plant. Especially the manual adaption of the automation systems causes high costs and significant downtimes. Here, an approach for an automatic adaption of the automation system is presented. The major challenges for an automatic adaptability of the automation system are (i) dynamically modifiable networks, (ii) a real-time middleware transporting variables within the network independently of the automation topology, and (iii) a semantic-based mechanism that allows one plant module to identify which signals are needed from another module. This paper describes a real-time middleware for industrial automation (mINA). It focuses especially on problem (iii), the mechanism to discover and identify required process signals. The functionality is based on a newly defined description language (mINA-DL), i.e. the middleware can use further semantic information about the signals. The middleware (ii) communicates by means of a real-time publish/subscribe concept and provides OPC UA compliance which also allows an easy integration with the manufacturing execution system (MES). Furthermore, a first prototypical implementation of the middleware is described and assessed using a test environment.

This paper describes a layer-2 based auto-configuration of topologically addressed redundant network structures, with an inherent dynamic redundancy management technique for loop prevention. A PC-based emulation technique is proposed for concept validation.

This paper investigates the potential of the emerging Ethernet audio video bridging (AVB) in industrial networks. An analytical model of AVB is described, and AVB's priority queuing (PQ) and credit-based shaper algorithms (CBQ) are evaluated and compared with standard Ethernet.

In factory communication systems, wireless networks are likely to complement wired automation networks, rather than replacing them. There is therefore an increasing interest in the way wireless and wired systems will interact and form a hybrid network. The hybrid network architecture proposed in this paper specifically addresses WLAN infrastructures in industrial environments. The paper discusses design challenges and describes the proposed system architecture and its main components.

Concerning its temporal behavior the latency caused by a handover from one access point (AP) to another is of particular interest for mobile industrial applications, e.g. automated guided vehicles, due to their real-time requirements in the range of a few milliseconds. With the advancements of wireless local area networks, fast roaming support has become one of the most important issues in IEEE 802.11. The IEEE 802.11r standard amendment has been specified to address roaming capabilities of real-time applications with an attempt to minimize BSS transition time while still providing the 802.11i security and 802.11e QoS. 802.11r permits seamless connectivity with a fast and secure handover from one AP to another within the same mobility domain. It provides an opportunity to derive encryption keys prior to a reassociation to reduce the connectivity loss during the handover. It also provides features for resource reservation and central mobility management. This paper presents an implementation of 802.11r based on a Linux operating system. It uses a softMAC approach that allows moving the processing of MAC layer management entity (MLME) from kernelspace to userspace. Measurement results show the performance gain of 802.11r as compared to a legacy implementation in terms of a handover time reduction, which is a core requirement of wireless industrial networks.

After the introduction of fieldbus technology, real-time Ethernet (RTE) systems now form the second generation of industrial communication systems (2G ICS). A lot of different approaches for RTEs appeared during the last years, most of them optimized for specific use cases or application domains. From a user's perspective, the transition from a proved fieldbus system to a RTE only makes sense, if multiple system properties are improved significantly in comparison to the state-of-the-art. In order to address such main requirements of machine builders, we introduced three building blocks as key components for a generic RTE system, these includes topology-based addressing, optimized datagram transfer, and synchronous scheduling.

This paper evaluates the performance of IEEE 802.15.4 for industrial wireless sensor networks. The IEEE 802.15.4 protocol has got the ability to provide real time data transmission in wireless sensor networks using guaranteed time slots (GTS) as medium access control mechanism. According to the standard, a maximum of 7 GTSs can be allocated in one superframe. All GTSs are exclusively dedicated to a corresponding node. Hence, the GTS mechanism is rather limited regarding the number of nodes and the needed scalability is missing. In this paper we introduce a new scheduling algorithm called ldquoEarliest Due Date GTS Allocationrdquo which can be implemented at the medium access control layer. Using this scheduling scheme and an appropriate scheduler, the GTS mechanism is enhanced, in order to enable a deployment in large scale networks with real-time requirements.

This paper describes a novel method for layer-2 auto-configuration of realtime Ethernet networks. Our approach is able to roll out local MAC addresses to the involved devices as well as to discover the topology automatically on top of LLDP. The description of the complete network topology is realized with a minimum amount of data and includes a systematically propagation towards the topology manager. A model-driven development approach has been adopted to verify the concept by using simulation technique.

The evolution of industrial communication inexorably moves to Industrial Ethernet networks. One important reason for using Ethernet at the shop floor is to participate on the continuous advancements of standard Ethernet. Thus it seems to be the logical next step to change the bit rate from Fast Ethernet to Gigabit Ethernet to achieve better performance. The question is, how the cycle time as a relevant performance metrics of industrial automation systems can profit from increasing the bit rate to 1 Gbps. Because of its importance for the industrial automation domain this paper focuses on line topology. The analysis is based on EtherCAT and PROFINET, which are two popular representatives of different architectures for high performance Industrial Ethernet networks.

The advantages of using IEEE 802.11-based wireless local area networks (WLAN) in industrial automation applications are substantial and comprise a higher flexibility, greater mobility and reduced maintenance costs. However, the currently used medium access mechanism makes WLANs non-deterministic and hence not suitable for industrial real-time traffic. The new amendment IEEE 802.11e introduces the HCF controlled channel access (HCCA) for parameterized QoS and the enhanced distributed channel access (EDCA) for prioritized QoS. This paper evaluates the performance of the HCCA in an industrial automation network with real-time requirements by means of a simulation case study with the network simulator OPNET and compares the results with the EDCA in terms of latency in various scenarios.

Ethernet has become so popular that it has also been further developed/or use at field level in automation technology under realtime conditions. However, for reasons of function and investment protection, the introduction of realtime Ethernet in automation solutions is likely to be a gradual process. Suitable solutions for the integration of existing fieldbus technology into the realtime Ethernet network are therefore required. This paper describes two possible integration concepts of the PROFINET IO realtime Ethernet standard using INTERBUS and PROFIBUS as an example. It shows that it is possible, despite very different device models of the considered fieldbus systems, to implement a high level of integration

Focuses on the special requirements of the control-level within factory communication systems to transmit real-time data via a switched Ethernet network. A performance evaluation of switched Ethernet is presented by providing simulation results. The simulations study the influence of different network topologies as well as the scheduling algorithms first-come-first-served and priority queuing within devices and intermediate systems, like switches. Furthermore we suggest a bus-like topology to enable fieldbus-like cabling qualities. Moreover the paper considers the impact of the dwell time within the stations upon real-time behavior.