Knowledge-Driven Architecture Composition: Case-Based Formalization of Integration Knowledge to Enable Automated Component Coupling

Burzlaff, Fabian; Bartelt, Christian

doi:10.1109/icsaw.2017.54

Cited by 12 publications

(5 citation statements)

References 17 publications

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“…id Switch2Light namespace de.ma.mappings description "A mapping which connects a switch to a light so that the light is toggled by the switch " infoModelReferences { using de.ma.informationmodels.Switch;1.0.0 as Switch using de.ma.informationmodels.Light;1.0.0 as Light } mappingBlocks { from Switch to Light: de.ma.mappingblocks. Switch2Dimmer } Listing 9: Switch to Light Mapping Limitations: Although the presented case study does not seem to improve the overall integration process in the given example a lot, the proposed language is a first technical step towards facilitating the presented, bottom-up integration methods based on incomplete integration knowledge [10] [13]. This means that with a high number of already integrated function blocks the described integration process can be automated based use-case specific semantics.…”

Section: Fig 4: Inmatch Prototype Utilized As Tool-support For Mappimentioning

confidence: 97%

“…Need: As a consequence, integration knowledge between provided and required interfaces is only persistent within software adapters and is currently not being captured, shared and reused [9]. Therefore, a novel engineering method called "Knowledge-driven Architecture Composition" (KDAC) for bottom-up IoT device integration was introduced [10]. The novelty of this method lies within the incremental formalization of semantic integration knowledge for IoT devices in addition to programming iterative software adapters.…”

Section: Introductionmentioning

confidence: 99%

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A Mapping Language for IoT Device Descriptions

Burzlaff

Ackel²,

Bartelt

2019

2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)

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Component models for IoT devices regain popularity. As more and more devices must be semantically connected within IoT platforms, digital abstractions for these devices are needed. For this purpose, textual device descriptions which encapsulate device-specific characteristics are a suitable candidate. Such component descriptions formally describe a device's information model as well as the offered functionality in a standardized way. However, smart IoT platforms mainly solve user goals by composing various IoT devices in a suitable manner. Current IoT descriptions, such as Eclipse Vorto do not address this need at all. In this paper, we introduce a formal mapping language that allows to capture functional interaction semantics already during device integration time. Our evaluation shows that only few mapping elements are needed to define functional mappings between operations as well as to capture the underlying communication pattern.

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Section: Fig 4: Inmatch Prototype Utilized As Tool-support For Mappimentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

A Mapping Language for IoT Device Descriptions

Burzlaff

Ackel²,

Bartelt

2019

2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)

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“…Burzlaff and Bartelt [59] focus on the IoT's impact on production processes. Specifically, languages with normalized semantics may improve automation in the component integration process, thereby simplifying manual integration (e.g., a 'plug and play' approach).…”

Section: Yellow Clustermentioning

confidence: 99%

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Manesh

Pellegrini

Marzi

et al. 2021

IEEE Trans. Eng. Manage.

184

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Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences.

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“…The dynamic view of our reference architecture is influenced by the applied integration method. Here, we use the "Knowledge-driven Architecture Composition" (KDAC) approach [17], [19]). The KDAC approach can be described as an interface integration method where integration knowledge is formalized per usecase.…”

Section: Dynamic Viewmentioning

confidence: 99%

MergePoint: A Graphical Web-App for Merging HTTP-Endpoints and IoT-Platform Models

Burzlaff

Bongarth²,

Grottker³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

Self Cite

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More and more devices are connected to Internet of Things Platforms in various application domains. The resulting device integration effort is moderated by the concrete integration syntax and the technical abilities of the device integrator. Therefore, researchers from various communities have been investigating and designing component coupling architectures to achieve interoperability for more than 30 years. Emerging Smart Home scenarios challenges classical integration approaches as no single formal integration standard exists. In this paper we introduce a reference architecture called MergePoint that automates HTTP-Endpoint integration with smart home platforms such as openHAB in a plug-and-play manner. Based on a prototypical system implementation, our empirical evaluation demonstrates that average integration time can be reduced by 78% and average tool usability score is increased by 65% compared to textual integration approaches. MergePoint can serve as a reference implementation for practitioners that want to automate the integration between HTTP-Endpoints and IoT Platform Models.

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Knowledge-Driven Architecture Composition: Case-Based Formalization of Integration Knowledge to Enable Automated Component Coupling

Cited by 12 publications

References 17 publications

A Mapping Language for IoT Device Descriptions

A Mapping Language for IoT Device Descriptions

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

MergePoint: A Graphical Web-App for Merging HTTP-Endpoints and IoT-Platform Models

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