Enabling edge-driven Dataspace integration through convergence of distributed technologies

Parwinder Singh*, Michail J. Beliatis, Mirko Presser

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperReviewResearchpeer-review

1 Citation (Scopus)

Abstract

Dataspace and emerging technologies play a key role in developing value chain systems using cross-domain data, services and systems integration. Therefore, this study has conducted a comprehensive literature review for six years (2017–2022) on the convergence of Internet of Things (IoT), Artificial Intelligence (AI) and Distributed Ledger (Blockchain) technologies for supporting Dataspace integration efforts at the Edge. As an outcome, this study has identified relevant challenges that include heterogeneity, integration and interoperability, distributed security, trust, scalability, and resource management. It has also been found that very limited research covers the architectural aspects of distributed edge in the context of the convergence of technologies for Dataspace integration purposes. Therefore, this study has proposed an architectural framework – Distributed Edge Network Operations-oriented Semantic (DENOS) model that extends the traditional Cloud–Edge-Device architecture with three new layers – Semantic, Convergence, and Dataspace integration. In addition, the model leverages the power of semantic modelling (i.e., Processing, Service, and Data) context, which enables the model to have a dynamic implementation context to suit the diverse needs of target use cases. To showcase the validation of the model, a use case related to the digital traceable operation of the wind energy domain has been presented. The objective of the DENOS model is to enable Dataspace integration to build edge-enabled value chain networks. Thus, it contributes to secure and semantic integration using the convergence of resources and technologies, cross-domain collaboration, reusability and data-driven decision-making of resources.

Original languageEnglish
Article number101087
JournalInternet of Things (Netherlands)
Volume25
ISSN2542-6605
DOIs
Publication statusPublished - Apr 2024

Keywords

  • Artificial Intelligence (AI)
  • Blockchain
  • Convergence of technologies
  • Data space
  • Distributed ledger technology
  • Edge computing
  • Integration
  • Internet of Things (IoT)
  • Interoperability
  • NGSI-LD
  • Resource pooling
  • Semantic context

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