Autonomy is today a widely discussed topic. Despite the already impressive technical possibilities, autonomy will still happen stepwise in industry. When it comes to paving the way toward autonomy in industry, it is important to define an appropriate taxonomy of autonomy levels from an industry perspective. Based on such a basic taxonomy, this paper suggests a process how to apply it to specific industrial systems. Exemplarily, an application to autonomous plants is sketched. Besides, enabling technologies required toward autonomy are discussed, as well as some implications of autonomy in industry.

Building automation (BA) systems usually consist of a multitude of devices, which are often based on different technologies and have to be integrated with each other. To facilitate the engineering of multi-technology BA systems, we propose a semantic-based engineering approach, e.g., based on VDI 3813 guideline, to specify BA functionality in a technology-independent way. This reduces the need for using various tools and manually configuring and integrating devices. Still, the challenge of mapping and commissioning such semantic-based projects to specific technologies remains. This paper tackles this challenge by proposing a set of algorithms to (semi-) automatically map VDI 3813 semantic concepts to various technologies used in BA systems, such as KNX and ZigBee. The realization of these algorithms in a modular and extensible tool architecture is proposed. This tool offers services to enable multi-technology BA systems both at engineering and operational phases.

In industrial automation, unexpected failures often generate high direct and indirect costs. To achieve high availability, the critical parts of the system are typically redundant. M-out-of-N (MooN) redundancy is a widespread redundancy pattern because it offers low failover times. This pattern has however two major disadvantages. First, the voter, an essential entity in MooN patterns, is itself a single point of failure. Second, it introduces delay to the control process and significant network load when deployed with multiple voters. This article proposes new MooN redundancy patterns for distributed control systems. These eliminate the voter as a single point of failure and reduce the network load and delay of the MooN redundancy. For each of these patterns we introduce an algorithm, which computes a near-minimum instance for the MooN problem. We validate our solution against minimum values and present a case study giving the delays introduced through our redundancy patterns and the induced network load.

This paper presents optimization techniques for implementing software-based redundancy in industrial control devices. Initially, a brief survey of software-based state replication techniques with a special focus on their applicability in industrial control devices is conducted. The scalability, predictability and low latency of the technique are of particular interest in this case. Based on this survey, an analytic evaluation of different implementation alternatives is performed. As part of this analysis, a novel state replication algorithm is introduced. The approach uses support from the compiler or runtime environment to detect changes in the application state with very low overhead. This information is used to replicate the state of an automation controller in a redundant setup. Lastly, experimental results using a prototype implementation of the presented technique demonstrate that the proposed novel approach is able to perform state replication with constant overhead.

In companies with a large portfolio of software or software-intensive products, functional overlaps are often perceived between independent products. In such situations it is advisable to systematically analyze the potential of systematic reuse and Software Product Lines. To this end, several domain analysis approaches, e.g., SEI Technical Probe, have been proposed to decide whether a set of products with a perceived functional overlap should be integrated into a single product line. Based on the principles of those approaches we devised our own approach. One important property is the inherent flexibility of the method to be able to apply it to four different application cases in industrial software products at ABB. In this paper we present our refined approach for domain analysis. The results and lessons learned are meant to support industrial researchers and practitioners alike. Moreover, the lessons learned highlight real-world findings concerning software reuse.

Abstract The upcoming IEEE 802.11s standard enables easy establishment and maintenance of wireless mesh networks in residential and enterprise scenarios. They, however, need special attention with respect to security. Due to multi‐hop communication and routing on layer 2 in mesh networks, attacks on the routing, selective forwarding, and eavesdropping on confidential data become relatively easy. To avoid such attacks, we introducedifferentiated securitywhich is based on protection levels associated with nodes in the network. Participation in the MAC layer routing is facilitated according to the respective protection level of a node. Using additional cryptographic protection our approach can also avoid unintentional disclosure of confidential data. Copyright © 2009 John Wiley & Sons, Ltd.

Large-scale attacks like distributed denial-of-service (DDoS) attacks still pose unpredictable threats to the Internet infrastructure and Internet-based business. Thus, many attack detection systems using various anomaly detection methods were developed in the past. These detection systems result in a set of anomalies detected by analysis of the traffic behavior. A realtime identification of the attack type that is represented by those anomalies simplifies important tasks like taking countermeasures and visualizing the network state. In addition, an identification facilitates a collaboration of distributed heterogeneous detection systems. In this paper, we first lay the foundations for a generalized identification system by establishing a model of those entities that form anomaly-based attack detection: large-scale attacks, anomalies, and anomaly detection methods. Based on this flexible model, an adaptable and resource-aware system for the identification of large-scale attacks is developed that additionally offers an autonomous processing control.

Despite the many research activities that are performed in the field of attack prevention, detection, and mitigation, large-scale attacks like Distributed Denial-of-Service (DDoS) at-tacks still pose unpredictable threats to the Internet infras-tructure and Internet-based business today. This paper out-lines new mechanisms that facilitate a distributed real-time in-network attack detection. In addition, the foundations for a meaningful evaluation of large-scale detection mech-anisms by means of simulations are laid. 1.