Michael Falkenthal

Towards an integrated service-oriented reference enterprise architecture

New business information systems are integrating emerging cloud infrastructures with service-oriented platforms and intelligent user-centered mobile systems. Both architecture engineering and management of service-oriented enterprise architectures is complex and has to integrate synergistic disciplines like EAM - Enterprise Architecture and Management for Services & Cloud Computing, Semantic-based Decision Support through Ontologies and Knowledge-based Systems, Big Data Management, as well as Mobility and Collaboration Systems. It is necessary to identify affected decisions by runtime changes of a service-oriented runtime environment and architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted business categories, processes, applications, services, platforms and infrastructures. The paper describes a new Metamodel-based integration approach for Service-oriented Reference Enterprise Architectures.

Internet of things patterns

The development of the Internet of Things is gaining more and more momentum. Due to its widespread applicability, many different solutions have been created in all kinds of areas and contexts. These include solutions for building automation, industrial manufacturing, logistics and mobility, healthcare, or public utilities, for private consumers, businesses, or government. These solutions often have to deal with similar problems, for example, constrained devices, intermittent connectivity, technological heterogeneity, or privacy and security concerns. But the diversity makes it hard to grasp the underlying principles, to compare different solutions, and to design an appropriate custom implementation in the Internet of Things space. We investigated a large number of production-ready Internet of Things offerings to extract recurring proven solution principles into Patterns, of which five are presented in this paper. These Patterns address several problems. Device Gateway shows how to connect devices to a network that do not support the networks technology. Device Shadow explains how to interact with currently offline devices. With a Rules Engine, you can create simple processing rules without programming. Device Wakeup Trigger allows you to get a disconnected device to reconnect to a network when needed. Remote Lock and Wipe can secure devices and their data in case of loss.

Comparison of IoT platform architectures: A field study based on a reference architecture

The Internet of Things (IoT) is gaining increasing attention. The overall aim is to interconnect the physical with the digital world. Therefore, the physical world needs to be measured and translated into processible data. Further, data has to be translated into commands to be executed by actuators. Due to the growing awareness of IoT, the amount of offered IoT platforms rises as well. The heterogeneity of IoT platforms is the consequence of multiple different standards and approaches. This leads to problems of comprehension, which can occur during the design up to the selection of an appropriate solution. We tackle these issues by introducing an IoT reference architecture based on several state-of-the-art IoT platforms. Furthermore, the reference architecture is compared to three open-source and one proprietary IoT platform. The comparison shows that the reference architecture provides a uniform basis to understand, compare, and evaluate different IoT solutions. The considered state-of-the-art IoT platforms are OpenMTC, FIWARE, SiteWhere, and Amazon Web Services IoT.

A Detailed Analysis of IoT Platform Architectures: Concepts, Similarities, and Differences

The IoT is gaining increasing attention. The overall aim is to interconnect the physical with the digital world. Therefore, the physical world is measured by sensors and translated into processible data, and data has to be translated into commands to be executed by actuators. Due to the growing interest in IoT, the number of platforms designed to support IoT has risen considerably. As a result of different approaches, standards, and use cases, there is a wide variety and heterogeneity of IoT platforms. This leads to difficulties in comprehending, selecting, and using appropriate platforms. In this work, we tackle these issues by conducting a detailed analysis of several state-of-the-art IoT platforms in order to foster the understanding of the (i) underlying concepts, (ii) similarities, and (iii) differences between them. We show that the various components of the different platforms can be mapped to an abstract reference architecture, and analyze the effectiveness of this mapping.

Collaborative gathering and continuous delivery of DevOps solutions through repositories

Collaboration is a key aspect for establishing DevOps-oriented processes because diverse experts such as developers and operations personnel need to efficiently work together to deliver applications. For this purpose, highly automated continuous delivery pipelines are established, consisting of several stages and their corresponding application environments (development, test, production, etc.). The DevOps community provides a huge variety of tools and reusable artifacts (i.e. DevOps solutions such as deployment engines, configuration definitions, container images, etc.) to implement such application environments. This paper presents the concept of collaborative solution repositories, which are based on established software engineering practices. This helps to systematically maintain and link diverse solutions. We further discuss how discovery and capturing of such solutions can be automated. To utilize this knowledge (made of linked DevOps solutions), we apply continuous delivery principles to create diverse knowledge base instances through corresponding pipelines. Finally, an integrated architecture is outlined and validated using a prototype implementation.

Requirements for a collaborative formulation process of evolutionary patterns

Within distributed joint research projects, it is necessary to align many kinds of engineering efforts across different work packages within the considered domain. Every project member has his own visions, expectations and experience that must be respected and integrated throughout the whole project duration. Especially in large research consortia, multidisciplinary backgrounds and different working practices need to collaborate and exchange information. Our approach applies the idea of using design patterns as interdisciplinary communication medium, especially for describing and explaining the current application domain and its characteristics. This work presents considerations from two pattern experts workshops that analyzed current pattern formulation and pattern language structuring processes with regard to their suitability to engineering practices within distributed research projects. The idea of using patterns as interdisciplinary communication medium was considered as useful. Additional challenges that were faced with current pattern derivation processes were extracted and formulated as requirements that found the basis for deriving the concept of a collaboratively evolutionary pattern library.

OpenTOSCA for the 4th Industrial Revolution: Automating the Provisioning of Analytics Tools based on Apache Flink

The 4th industrial revolution entails new levels of data driven value chain organization and management. In industrial environments, the optimization of whole production lines based on machine learning algorithms allow to generate huge business value. Still, one of the open challenges is how to process the collected data as close to the data sources as possible. To fill this gap, this paper presents an OpenTOSCA-based toolchain that is capable of automatically provisioning Apache Flink as a holistic analytics environment altogether with specialized machine learning algorithms. This stack can be deployed as close to the production line as possible to enable data driven optimization. Further, we demonstrate how the analytics stack can be modeled based on TOSCA to be automatically provisioned considering specific mock services to simulate machine metering in the development phase of the algorithms.

Industrial Data Sharing with Data Access Policy

In current industrial settings, data is dispersed on numerous devices, systems and locations without integration and sharing capabilities. With this work, we present a framework for the integration of various data sources within an industrial setting, based on a mediating data hub. Within the data hub, data sources and sinks for this industrial application are equipped with data usage policies to restrict and enable usage and consumption of data for shared analytics. We identify such policies, their requirements and rationale. This work addresses an industrial setting, with manufacturing data being the primary use-case. Requirements for these policies are identified from existing use-cases and expert domain knowledge. The requirements are identified as reasonable via examples and exemplary implementation.

Pattern research in the digital humanities: how data mining techniques support the identification of costume patterns

Costumes are prominent in transporting a character’s mood, a certain stereotype, or character trait in a film. The concept of patterns, applied to the domain of costumes in films, can help costume designers to improve their work by capturing knowledge and experience about proven solutions for recurring design problems. However, finding such Costume Patterns is a difficult and time-consuming task, because possibly hundreds of different costumes of a huge number of films have to be analyzed to find commonalities. In this paper, we present a Semi-Automated Costume Pattern Mining Method to discover indicators for Costume Patterns from a large data set of documented costumes using data mining and data warehouse techniques. We validate the presented approach by a prototypical implementation that builds upon the Apriori algorithm for mining association rules and standard data warehouse technologies.

Utilising the Tor Network for IoT Addressing and Connectivity

For Internet of Things (IoT) devices and cyber-physical systems (CPS), it is required to connect them securely and reliably to some form of cloud environment or computing entity for control, management and utilisation. The Internet is a suitable, standardized, and proven means for the connection of IoT devices in various scenarios. Connection over the Internet utilises existing protocols, standards, technologies and avoids investment in new, specialised concepts. Thereby, this connection requires a transparent addressing schema which is commonly TCP/IP, using domain names and IP addresses. However, in industrial, commercial and private networks, the addressability and connectability/connectivity is often limited by firewalls, proxies and router configurations utilising NAT. Thus, the present network configurations hinder the establishment of connections between IoT devices across different locations. Therefore, the method for connecting IoT devices in a client-server configuration proposed herein utilises the Tor (previously: The onion router/routing) network for addressing of and secured communication to IoT and CPS devices. It is an overlay protocol that was designed to allow for robust and anonymous communication. The benefit of this approach is to enable addressability and connectivity of IoT devices in firewalled and potentially unknown and changing network environments, thus allowing for IoT devices to be used reliably behind firewalls as long as outgoing communication is not