Reference Architecture Research Articles

On reference architectures

AbstractA reference architecture is a key architectural asset for the systems engineer, that intends both to simplify its work and to guarantee the exhaustiveness of the coverage of its system analyses. This paper proposes formal definitions for a reference architecture, based on the theory of abstract interpretation that formalizes the notion of abstraction, which covers respectively large and small‐scale families of systems. These definitions are illustrated by automotive, building, and mining case studies.

Development and Implementation of a Cognitive Cloud Assistant for Optimal Cloud Service Provider Selection

Abstract This paper explores the design and implementation of a cognitive assistant powered by cloud computing. We begin by reviewing existing cloud service providers and assistant solutions. Building on this foundation, we define a set of requirements for our cognitive assistant and utilize them to guide the development process. To validate the functionality of our creation, we compare its outputs with established reference architectures.

Reference architecture design and evaluation for digitalization of underground mining

Digitalization of underground mining operations requires interaction and interoperability between multiple stakeholders and their technical systems. A reference architecture (RA) facilitating design of multi-stakeholder digital solutions for underground mining would be valuable design knowledge for mining industry digitalization activities and would facilitate the design of concrete architectures to the underground mining context. The main contribution of this work is RA design, which is missing in the current research literature. The RA has empirical foundation on the implementation architectures of two prototypes, which were demonstrated and evaluated in an underground mining environment. The prototypes were evaluated based on several design science research evaluation criteria (feasibility, efficiency, robustness, operability) for fulfilling architectural concerns of related stakeholders. Digital Twin-based modeling, MQTT-based messaging, high accuracy location monitoring of vehicles with Lidars, reliable communication with 5G SA network, and utilization of safety zones and safety messaging for enabling emergency stops were identified as important aspects for RA design. Digital Twin (DT)-based data models focusing on the modeling of mining site, moving vehicles, communication data, and related equipment for the underground mining context may be considered as an additional contribution of our study.

The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc. For enabling communication and cooperation between actors from different domains using different methodologies, languages and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystems and all its components in structure, function and relationships in the necessary detail ranging from elementary particles up to the universe. That way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business view of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture.

Design and implementation of a machine log for PBF-LB/M on basis of IoT communication architectures and an ETL pipeline

Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M) has gained more industrial relevance and already demonstrated applications at a small series scale. However, its widespread adoption in various use cases faces challenges due to the absence of interfaces to established Manufacturing Execution Systems (MES) that support customers in the predominantly data-driven quality assurance. Current state-of-the-art PBF-LB/M machines utilize communication architectures, such as OPC Unified Architecture (OPC UA), Message Queuing Telemetry Transport (MQTT) and Representational State Transfer Application Programming Interface (REST API). In the context of the Reference Architecture Model Industry 4.0 (RAMI 4.0) and the Internet of Things (IoT), the assets, particularly the physical PBF-LB/M machines, already have an integration layer implemented to communicate data such as process states or sensor values. Missing is an MES component acting as a communication and information layer. To address this gap, the proposed Extract Transform Load (ETL) pipeline aims to extract relevant data from the fabrication of each build cycle down to the level of scan vectors and additionally to register process signals. The suggested data schema for archiving each build cycle adheres to all terms defined by ISO/TC 261—Additive Manufacturing (AM). In relation to the measurement frequency, all data are reorganized into entities, such as the AM machine, build cycle, part, layer, and scan vector. These scan vectors are stored in a runtime-independent format, including all metadata, to be valid and traceable. The resulting machine log represents a comprehensive documentation of each build cycle, enabling data-driven quality assurance at process level.

Analysis and design framework for the development of indoor scene understanding assistive solutions for the person with visual impairment/blindness

This paper discusses the challenges of the current state of computer vision-based indoor scene understanding assistive solutions for the person with visual impairment (P-VI)/blindness. It focuses on two main issues: the lack of user-centered approach in the development process and the lack of guidelines for the selection of appropriate technologies. First, it discusses the needs of users of an assistive solution through state-of-the-art analysis based on a previous systematic review of literature and commercial products and on semi-structured user interviews. Then it proposes an analysis and design framework to address these needs. Our paper presents a set of structured use cases that help to visualize and categorize the diverse real-world challenges faced by the P-VI/blindness in indoor settings, including scene description, object finding, color detection, obstacle avoidance and text reading across different contexts. Next, it details the functional and non-functional requirements to be fulfilled by indoor scene understanding assistive solutions and provides a reference architecture that helps to map the needs into solutions, identifying the components that are necessary to cover the different use cases and respond to the requirements. To further guide the development of the architecture components, the paper offers insights into various available technologies like depth cameras, object detection, segmentation algorithms and optical character recognition (OCR), to enable an informed selection of the most suitable technologies for the development of specific assistive solutions, based on aspects like effectiveness, price and computational cost. In conclusion, by systematically analyzing user needs and providing guidelines for technology selection, this research contributes to the development of more personalized and practical assistive solutions tailored to the unique challenges faced by the P-VI/blindness.

Flexible Deployment of Machine Learning Inference Pipelines in the Cloud–Edge–IoT Continuum

Currently, deploying machine learning workloads in the Cloud–Edge–IoT continuum is challenging due to the wide variety of available hardware platforms, stringent performance requirements, and the heterogeneity of the workloads themselves. To alleviate this, a novel, flexible approach for machine learning inference is introduced, which is suitable for deployment in diverse environments—including edge devices. The proposed solution has a modular design and is compatible with a wide range of user-defined machine learning pipelines. To improve energy efficiency and scalability, a high-performance communication protocol for inference is propounded, along with a scale-out mechanism based on a load balancer. The inference service plugs into the ASSIST-IoT reference architecture, thus taking advantage of its other components. The solution was evaluated in two scenarios closely emulating real-life use cases, with demanding workloads and requirements constituting several different deployment scenarios. The results from the evaluation show that the proposed software meets the high throughput and low latency of inference requirements of the use cases while effectively adapting to the available hardware. The code and documentation, in addition to the data used in the evaluation, were open-sourced to foster adoption of the solution.

Improving emergency and disaster response management through bidirectional communication between citizens and decision-makers – A field test on the coordination of spontaneous volunteers

Cooperation between different stakeholders plays an important role in managing crises and disasters. The software tools used must also support cooperation and the mutual exchange of information. The bidirectional exchange of information between the population and official agencies poses a particular challenge. In this paper, we present a software demonstrator for the coordination of spontaneous volunteers and its evaluation as part of an overarching research project to gain design knowledge for the development of interconnected systems in disaster management. We describe how the system demonstrator was instantiated on the basis of our existing design knowledge from technical requirements and reference architecture and show the respective interfaces for the stakeholders involved. As the main contribution of the paper, we describe the implementation of a field test to evaluate the demonstrator and present the results in terms of usability and perceived usefulness, which we obtained using a methodologically sound questionnaire.

Enhancing strategy for Industry 4.0 implementation through maturity models and standard reference architectures alignment

PurposeA maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.Design/methodology/approachThree steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.FindingsThe study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.Research limitations/implicationsFindings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.Practical implicationsTo fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.Originality/valueThe novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

Reference architecture design for developing data management systems in smart farming

The traditional data management systems prove inadequate to handle the volume, velocity, and variety of the data within farm business processes. Smart farming technologies offer advanced data management systems as a practical solution to these challenges. However, data is complex and originates from many sources; hence many aspects of data must be considered during the data management design of smart farming systems. This study proposes a reference architecture for data management in smart farming, developed through domain analysis and architecture modeling approaches. The domain analysis provides insights into the common and variant features and modules of the smart farming system, resulting in a blueprint representing family features across various smart farming domains. The effectiveness of the proposed reference architecture has been evaluated through two case studies, demonstrating its efficacy in designing data management systems for smart farming. The study found that the percentage of reused modules in the case studies, compared to the provided reference architecture, was 82.6%. The outcomes of this research will pave the way for further exploration in smart farming, particularly addressing data management issues within smart farming systems.

Secured intelligent transportation with privacy retention through blockchain framework

The Secured Independent Intelligent Transport System (SIITS) is poised to revolutionize traditional transport management systems, leveraging autonomous vehicles (AVs) connected through an open-channel Internet to link Traffic Command Centers (TCCs), Road Side Units (RSUs), and AVs within the SIITS framework. However, this reliance on the Internet exposes users to various security risks, safety vulnerabilities, and other challenges that impede the progress of SIITS applications. In this method, ensuring robust security management and trustworthiness is paramount for the long-term adoption of this innovative trend. While previous efforts have focused on integrating security methods from multiple disciplines into a unified reference design, this article presents a reference architecture primarily centered around ITS safety. Additionally, the article introduces a proposed framework for enhancing ITS safety, addressing the confidence issues. To further address these challenges, the article offers categorization of goods, Big Data methods and services, and validates the utility of ITS business analytics for corporate applications through a groundbreaking multi-tier ITS security architecture.

Can GPU performance increase faster than the code error rate?

Graphics processing units (GPUs) are the reference architecture to accelerate high-performance computing applications and the training/interference of convolutional neural networks. For both these domains, performance and reliability are two of the main constraints. It is believed that the only way to increase reliability is to sacrifice performance, e.g., using redundancies. We show in this paper that this is not always the case. As a very promising result, we found that most GPUs performance improvements also bring the benefit of increasing the number of executions correctly completed before experiencing a silent data corruption (SDC). We consider four different common GPUs’ performance optimizations: architectural solutions, software implementations, compiler optimizations, and threads degree of parallelism. We compare different implementations of a variety of parallel codes and, through beam experiments and applications profiling, we show that the performance improvement typically (but not necessarily) increases the GPU SDC rate. Nevertheless, for the vast majority of the configurations the performance gain is much higher than the SDC rate increase, allowing to process a higher amount of correct data. As we show, the programmer choices can increase up to 25×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$25\ imes {}$$\\end{document} the number of correctly completed executions without redesigning the algorithm nor including specific hardening solutions.

CANDIL: A federated data fabric for network analytics

The availability of data sources during the Big Data era provides the opportunity for new analytical applications in the networking domain, which are envisioned as one of the main enablers of the future autonomous networks. But the proliferation of heterogeneous data sources has resulted into a sea of data silos, in which finding data, understanding data, and dealing with the complexities of each data source becomes a challenge. Aiming to tackle the connection of data silos, the data fabric has appeared as a new paradigm that provides a uniform access to all the data, abstracting consumers from the underlying complexities of the data sources. In this regard, the knowledge graph has raised as a promising solution that can integrate data from heterogeneous silos based on common concepts captured in ontologies. Building upon knowledge graph standards, this paper introduces CANDIL, a federated data fabric to support the integration of data from distributed systems, mainly focused on networking domain aspects. CANDIL defines an ontology that captures network topology and interface concepts, along with a reference architecture to ingest and integrate data in a federated knowledge graph that spans across the Edge-Cloud continuum. The proposal is validated with a prototype implementation and two example use cases of network analytics.

Medium-Level Architectures for Digital Twins: Bridging Conceptual Reference Architectures to Practical Implementation in Cloud, Edge and Cloud–Edge Deployments

The integration of Digital Twins (DTs) is becoming increasingly important in various industries. This entails the need for a comprehensive and practical IT infrastructure framework. This paper presents a modifiable medium-level architecture that serves as a link between established reference architectures such as RAMI 4.0 and the pragmatic implementation of Digital Twins. The functionalities of an IT infrastructure are considered, and functional hardware and software components for fulfilling these are described. The proposed architecture is suitable for various deployment scenarios, including local, cloud and hybrid cloud–edge configurations. In order to improve the applicability of the medium-level architecture, a step-by-step procedure is also proposed, which helps to transfer the overarching requirements for a Digital Twin into a suitable IT infrastructure. Finally, the results are demonstrated by an exemplary application to a two-stage industrial gearbox.

A model-based reference architecture for complex assistive systems and its application

Complex assistive systems providing human behavior support independent of the age or abilities of users are broadly used in a variety of domains including automotive, production, aviation, or medicine. Current research lacks a common understanding of which architectural components are needed to create assistive systems that use models at runtime. Existing descriptions of architectural components are focused on particular domains, consider only some parts of an assistive system, or do not consider models at runtime. We have analyzed common functional requirements for such systems to be able to propose a set of reusable components, which have to be considered when creating assistive systems that use models. Such components constitute a reference architecture that we propose within this paper. To validate the proposed architecture, we have expressed the architectures of two assistive systems from different domains, namely assistance for elderly people and assistance for operators in smart manufacturing in terms of compliance with such architecture. The proposed reference architecture will facilitate the creation of future assistive systems.

Towards enhanced monitoring framework with smart predictions

Abstract Context: Predicting security and trust vulnerabilities and issues is crucial for IoT interconnected systems and ecosystems, especially when integrating new, third-party or open-source components. Objective: One way to ensure timely predictions is by using a smart monitoring framework to continuously verify functional and non-functional property violations during the executions of the systems and their components. Method: This paper presents a set of guidelines for the Smart Monitoring Framework definition and its application process. Results and Conclusion: The paper provides the reference architecture of the Smart Monitoring Framework and its possible implementation to promptly detect suspicious behavior or property violations. The paper also illustrates how the provided implementation satisfies the defined guidelines by design.

Der qualitätsbewusste Digitale Zwilling

Abstract Connecting a digital twin to its associated cyber-physical system improves system knowledge and supports effective operation. The presented reference architecture includes a service component that manages different services to optimize process quality. Two exemplary services illustrate the potential of this reference architecture. A model-driven approach with design and runtime models is used to increase the level of abstraction.

Multiphysics and multi-scale design and analysis of nuclear thermal propulsion pellet bed reactor based on spherical cermet fuel element

Due to the advantages of high thrust and high specific impulse, nuclear thermal propulsion (NTP) is a preferred near-term rocket engine technology for future Mars missions. This article introduces the reactor design based on spherical cermet fuel element, with the aim of studying the feasibility of applying this new fuel in NTP system. First, design requirements are determined based on the unique features of NTP. In terms of neutronics, the effect of rocket launch accidents and fuel loss caused by high-temperature hydrogen are considered. Thermal hydraulics refer to the requirements of NASA's Mars Design Reference Architecture 5.0 (DRA 5.0) for impulse, thrust, and thrust to weight ratio. Second, based on the requirements above, the optimal reactor configuration parameters are obtained with the goal of maximizing the thrust to weight ratio: reactor radius 51.1 cm, height 106 cm, aspect ratio 1.04, reflector 13 cm, and reactor mass 3940 kg. Finally, the performances of the optimal reactor design are analyzed. The neutron spectrum shows a characteristic of fast neutron spectrum, and fuel loss analysis shows that the core can withstand a fuel mass loss of about 4 wt%. In addition, the core axial and radial power distribution are calculated, with an overall power peak factor of 1.26. The thermal hydraulic calculation provides a range of core operating conditions that satisfy the design requirements of DRA 5.0 and temperature, with power of 620 ∼ 950 MW and flow rate of 16 ∼ 24 kg/s. Compared with the ANL200/2000 reactor using prismatic cermet, it has the advantage of higher specific impulse. The main disadvantage is the large pressure drop, which prevents it from being applied to the scenarios of high power and high thrust. Therefore, for NTP reactor using spherical cermet elements, it should be applied to low to medium power scenarios.

Enhancing Industrial Digitalisation through an Adaptable Component for Bridging Semantic Interoperability Gaps

Digital transformation has a great effect on industries but also in the perception of their products with high consequences on society as a whole, as driver for innovation. However, there are still many barriers to the adoption of digital technologies, especially in small and medium-sized enterprises (SMEs). In the present study we propose a new software component that facilitates the adoption of industrial reference architectures (RAs) based on the semantic interoperability concept. Among these RAs, FIWARE has become a key enabler for flexible and resource effective digitalisation of shop floor processes. The proposed software component aims to enable full interoperability between these more widely used technologies and industrial standards and protocols such as OPC UA. As a result, a flexible, open, and adaptable implementation assists the automatic translation of messages from different standards enabling semantic interoperability of shop floor processes. The component aims to enable industrial SMEs to bring current barriers to digitalisation towards a more human-centred, resilient, and sustainable industry and society.

Risk-based safety scoping of adversary-centric security testing on Operational Technology

Due to the recent increase in cyber attacks targeting Critical National Infrastructure, governments and organisations alike have invested considerably into improving the security of their underlying infrastructure, commonly known as Operational Technology (OT). The use of adversary-centric security tests such as vulnerability assessments, penetration tests and red team engagements has gained significant traction due to these engagements’ goal to emulate threat actors in preparation for genuine cyber attacks. Challenges arise, however, when performing security tests on these as the nature of OT requires additional safety and operation risks to be considered. This paper proposes a framework for incorporating the assessment of safety and operational risks within an overall scoping methodology for adversary-centric security testing in OT environments. Within this framework, we also propose a hybrid testing model derived from the Purdue Enterprise Reference Architecture and the Defense in Depth model to identify and quantify safety and operational risk at a per-layer level, separating high and low-risk layers and being subsequently used for defining the rules of engagement. As a result, this framework can aid vendors and clients in appropriately scoping adversary-centric security tests so that depth-of-testing is maximised while minimising the risk to safety and to the operational process. The framework is then evaluated through a qualitative study involving industry experts, confirming the framework’s validity for implementation in practice.