Informatik
Refine
Document Type
- Conference proceeding (40)
- Book chapter (11)
- Journal article (3)
Is part of the Bibliography
- yes (54) (remove)
Institute
- Informatik (54)
Publisher
- Springer (54) (remove)
Due to the consequential impact of technological breakdowns, companies have to be prepared to deal with breakdowns or even better prevent them. In today's information technology, several methods and tools exist to downscale this concern. Therefore, this paper deals with the initial determination of a resilient enterprise architecture supporting predictive maintenance in the information technology domain and furthermore, concerns several mechanisms on how to reactively and proactively secure the state of resiliency on several abstraction levels. The objective of this paper is to give an overview on existing mechanisms for resiliency and to describe the foundation of an optimized approach, combining infrastructure and process mining techniques.
While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
Software evolvability is an important quality attribute, yet one difficult to grasp. A certain base level of it is allegedly provided by service- and microservice-based systems, but many software professionals lack systematic understanding of the reasons and preconditions for this. We address this issue via the proxy of architectural modifiability tactics. By qualitatively mapping principles and patterns of Service Oriented Architecture (SOA) and microservices onto tactics and analyzing the results, we cannot only generate insights into service-oriented evolution qualities, but can also provide a modifiability comparison of the two popular service-based architectural styles. The results suggest that both SOA and microservices possess several inherent qualities beneficial for software evolution. While both focus strongly on loose coupling and encapsulation, there are also differences in the way they strive for modifiability (e.g. governance vs. evolutionary design). To leverage the insights of this research, however, it is necessary to find practical ways to incorporate the results as guidance into the software development process.
While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.
A configuration-management-database driven approach for fabric-process specification and automation
(2014)
In this paper we describe an approach that integrates a Configuration- Management-Database into fabric-process specification and automation in order to consider different conditions regarding to cloud-services. By implementing our approach, the complexity of fabric processes gets reduced. We developed a prototype by using formal prototyping principles as research methods and integrated the Configuration-Management-Database Command into the Workflow- Management-System Activiti. We used this prototype to evaluate our approach. We implemented three different fabric-processes and show that by using our approach the complexity of these three fabric-processes gets reduced.
The digital transformation is today’s dominant business transformation having a strong influence on how digital services and products are designed in a service-dominant way. A popular underlying theory of value creation and economic exchange that is known as the service-dominant (S-D) logic can be connected to many successful digital business models. However, S-D logic by itself is abstract. Companies cannot directly use it as an instrument for business model innovation and design in an easy way. To address this a comprehensive ideation method based on S-D logic is proposed, called service-dominant design (SDD). SDD is aimed at supporting firms in the transition to a service- and value-oriented perspective. The method provides a simplified way to structure the ideation process based on four model components. Each component consists of practical implications, auxiliary questions and visualization techniques that were derived from a literature review, a use case evaluation of digital mobility and a focus group discussion. SDD represents a first step of having a toolset that can support established companies in the process of service- and value-orientation as part of their digital transformation efforts.
Die digitale Transformation ist die heute vorherrschende geschäftliche Transformation, die einen starken Einfluss darauf hat, wie digitale Dienstleistungen und Produkte dienstleistungsdominant gestaltet werden. Eine beliebte zugrundeliegende Theorie der Wertschöpfung und des wirtschaftlichen Austauschs, die als dienstleistungsdominante Logik (S-D) bekannt ist, kann mit vielen erfolgreichen digitalen Geschäftsmodellen verbunden werden. Allerdings ist die S-D-Logik an sich abstrakt. Unternehmen können sie nicht ohne Weiteres als Instrument für die Innovation und Gestaltung von Geschäftsmodellen nutzen. Um dies zu ändern, wird eine umfassende Ideenfindungsmethode auf der Grundlage der S-D-Logik vorgeschlagen, die als service-dominantes Design (SDD) bezeichnet wird. SDD zielt darauf ab, Unternehmen beim Übergang zu einer service- und wertorientierten Perspektive zu unterstützen. Die Methode bietet eine vereinfachte Möglichkeit, den Ideenfindungsprozess auf der Grundlage von vier Modellkomponenten zu strukturieren. Jede Komponente besteht aus praktischen Implikationen, Hilfsfragen und Visualisierungstechniken, die aus einer Literaturrecherche, einer Anwendungsfallbewertung der digitalen Mobilität und einer Fokusgruppendiskussion abgeleitet wurden. SDD ist ein erster Schritt zu einem Toolset, das etablierte Unternehmen bei der Service- und Werteorientierung im Rahmen ihrer digitalen Transformation unterstützen kann.
Autonomous navigation is one of the main areas of research in mobile robots and intelligent connected vehicles. In this context, we are interested in presenting a general view on robotics, the progress of research, and advanced methods related to this field to improve autonomous robots’ localization. We seek to evaluate algorithms and techniques that give robots the ability to move safely and autonomously in a complex and dynamic environment. Under these constraints, we focused our work in the paper on a specific problem: to evaluate a simple, fast and light SLAM algorithm that can minimize localization errors. We presented and validated a FastSLAM 2.0 system combining scan matching and loop closure detection. To allow the robot to perceive the environment and detect objects, we have studied one of the best deep learning technique using convolutional neural networks (CNN). We validate our testing using the YOLOv3 algorithm.
Power line communications (PLC) reuse the existing power-grid infrastructure for the transmission of data signals. As power line the communication technology does not require a dedicated network setup, it can be used to connect a multitude of sensors and Internet of Things (IoT) devices. Those IoT devices could be deployed in homes, streets, or industrial environments for sensing and to control related applications. The key challenge faced by future IoT-oriented narrowband PLC networks is to provide a high quality of service (QoS). In fact, the power line channel has been traditionally considered too hostile. Combined with the fact that spectrum is a scarce resource and interference from other users, this requirement calls for means to increase spectral efficiency radically and to improve link reliability. However, the research activities carried out in the last decade have shown that it is a suitable technology for a large number of applications. Motivated by the relevant impact of PLC on IoT, this paper proposed a cooperative spectrum allocation in IoT-oriented narrowband PLC networks using an iterative water-filling algorithm.
The digitization of factories will be a significant issue for the 2020s. New scenarios are emerging to increase the efficiency of production lines inside the factory, based on a new generation of robots’ collaborative functions. Manufacturers are moving towards data-driven ecosystems by leveraging product lifecycle data from connected goods. Energy-efficient communication schemes, as well as scalable data analytics, will support these various data collection scenarios. With augmented reality, new remote services are emerging that facilitate the efficient sharing of knowledge in the factory. Future communication solutions should generally ensure connectivity between the various production sites spread worldwide and new players in the value chain (e.g., suppliers, logistics) transparent, real-time, and secure. Industry 4.0 brings more intelligence and flexibility to production. Resulting in more lightweight equipment and, thus, offering better ergonomics. 5G will guarantee real-time transmissions with latencies of less than 1 ms. This will provide manufacturers with new possibilities to collect data and trigger actions automatically.
An autonomous vehicle is a robotic vehicle with decision and action capability capable of performing assigned tasks without or with minimal human intervention. Autonomous cars have been in development for many years. The Society of Automotive Engineers (SAE International) published in 2014 a classification in five levels of driving automation, with level 0 corresponding to completely manual driving, and level 5 to an ideal dream where the vehicle would be able to navigate entirely autonomously for all missions and in all environments. This work addressed the navigation of an autonomous vehicle in general. We focus on one of the most complex scenarios of the road network and crossing of road intersections. In this paper, the critical features of autonomous intelligent vehicles are reviewed. Furthermore, the associated problems are presented, and the most advanced solutions are derived. This article aims to allow a novice in this field to understand the different facets of localization and perception problems for autonomous vehicles.
Rotating machinery occupies a predominant place in many industrial applications. However, rotating machines are often encountered with severe vibration problems. The measurement of these machines’ vibrations signal is of particular importance since it plays a crucial role in predictive maintenance. When the vibrations are too high, they often cause fatigue failure. They announce an unexpected stop or break and, consequently, a significant loss of productivity or an attack on the personnel’s safety. Therefore, fault identification at early stages will significantly enhance the machine’s health and significantly reduce maintenance costs. Although considerable efforts have been made to master the field of machine diagnostics, the usual signal processing methods still present several drawbacks. This paper examines the rotating machinery condition monitoring in the time and frequency domains. It also provides a framework for the diagnosis process based on machine learning by analyzing the vibratory signals.
In today’s education, healthcare, and manufacturing sectors, organizations and information societies are discussing new enhancements to corporate structure and process efficiency using digital platforms. These enhancements can be achieved using digital tools. Industry 5.0 and Society 5.0 give several potentials for businesses to enhance the adaptability and efficacy of their industrial processes, paving the door for developing new business models facilitated by digital platforms. Society 5.0 can contribute to a super-intelligent society that includes the healthcare industry. In the past decade, the Internet of Things, Big Data Analytics, Neural Networks, Deep Learning, and Artificial Intelligence (AI) have revolutionized our approach to various job sectors, from manufacturing and finance to consumer products. AI is developing quickly and efficiently. We have heard of the latest artificial intelligence chatbot, ChatGPT. OpenAI created this, which has taken the internet by storm. We tested the effectiveness of a considerable language model referred to as ChatGPT on four critical questions concerning “Society 5.0”, “Healthcare 5.0”, “Industry,” and “Future Education” from the perspectives of Age 5.0.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
Companies are continuously changing their strategy, processes, and information systems to benefit from the digital transformation. Controlling the digital architecture and governance is the fundamental goal. Enterprise Governance, Risk and Compliance (GRC) systems are vital for managing digital risks threatening in modern enterprises from many different angles. The most significant constituent to GRC systems is the definition of controls that is implemented on different layers of a digital Enterprise Architecture (EA). As part of the compliant aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper, we present a metamodel which links controls to the affected elements of a digital EA and supplies a way of expressing associated assessment techniques and results. We complement a metamodel with an expository instantiation of a control compliance cockpit in an international insurance enterprise.
New or adapted digital business models have huge impacts on Enterprise Architectures (EA) and require them to become more agile, flexible, and adaptable. All these changes are happening frequently and are currently not well documented. An EA consists of a lot of elements with manifold relationships between them. Thus changing the business model may have multiple impacts on other architectural elements. The EA engineering process deals with the development, change and optimization of architectural elements and their dependencies. Thus an EA provides a holistic view for both business and IT from the perspective of many stakeholders, which are involved in EA decision-making processes. Different stakeholders have specific concerns and are collaborating today in often unclear decision-making processes. In our research we are investigating information from collaborative decision-making processes to support stakeholders in taking current decisions. In addition we provide all information necessary to understand how and why decisions were taken. We are collecting the decision-related information automatically to minimize manual time intensive work as much as possible. The core contribution of our research extends a decisional metamodel, which links basic decisions with architectural elements and extends them with an associated decisional case context. Our aim is to support a new integral method for multi perspective and collaborative decision-making processes. We illustrate this by a practice-relevant decision-making scenario for Enterprise Architecture Engineering.
Enterprises and societies currently face essential challenges, and digital transformation can contribute to their resolution. Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies covering ecosystem partners. The advancement of new business models can be promoted with digital platforms and architectures for Industry 4.0 and Society 5.0. Therefore, products from the sector of healthcare, manufacturing and energy, etc. can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 and the design thinking approach is expected to promote and implement the digital platforms and digital products for healthcare, manufacturing and energy communities more efficiently. In this paper, we propose various cases of digital transformation where digital platforms and products are designed and evaluated for digital IT, digital manufacturing and digital healthcare with Industry 4.0 and Society 5.0. The vision of AIDAF applications to perform digital transformation in global companies is explained and referenced, extended toward the digitalized ecosystems such as Society 5.0 and Industry 4.0.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
Enterprises and societies currently face crucial challenges, while Industry 4.0 becomes important in the global manufacturing industry all the more. Industry 4.0 offers a range of opportunities for companies to increase the flexibility and efficiency of production processes. The development of new business models can be promoted with digital platforms and architectures for Industry 4.0. Therefore, products from the healthcare sector can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 is expected to promote and implement the digital platforms and robotics for healthcare and medical communities efficiently. In this paper, we propose that various digital platforms and robotics are designed and evaluated for digital healthcare as for manufacturing industry with Industry 4.0. We argue that the design of an open healthcare platform “Open Healthcare Platform 2030 - OHP2030” for medical product design and robotics can be developed with AIDAF. The vision of AIDAF applications to enable Industry 4.0 in the OHP2030 research initiative is explained and referenced, extended in the context of Society 5.0.