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May 7, 2026ACM Transactions on Internet of Things0 citations

A Context-Aware Middleware for FL-Enabled Collaboration in IoT-Enhanced Communities

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NPNikolaos PapadakisGBGeorgios BouloukakisKMKostas Magoutis

Key Points

  • This research aims to address interoperability issues in IoT smart communities through a new middleware solution.
  • Developed a context-aware middleware named ComDeX for federated IoT collaboration.
  • Utilized a property-graph data model for encoding IoT entities in pub/sub messages.
  • Implemented discovery and filtering via an advertisement-based federation.
  • Prototyped the solution on MQTT and NGSI-LD in a smart-port scenario.
  • Demonstrated faster and more efficient cross-community data exchange than existing methods.
  • Showcased capabilities for cross-community enrollment in non-IID FL experiments.
  • Exposed various coordination trade-offs for the DEE layer.

Abstract

The rapid growth of IoT-powered smart communities has created valuable, but siloed data, limited by interoperability and data-sovereignty concerns. We present ComDeX , a context-aware federated IoT middleware that enables selective, intelligent collaboration across communities. ComDeX uses a property-graph data model to encode IoT entities as context-rich pub/sub messages, discovered and filtered via an advertisement-based federation, so communities share only what is relevant while retaining control. To support collaborative intelligence, ComDeX adds a cross-organization Discovery → Eligibility → Enrollment (DEE) layer that enables discovery of FL tasks and clients, independent of the chosen FL runtime. We prototype ComDeX on MQTT and NGSI-LD and evaluate in a smart-port scenario, demonstrating faster and more efficient cross-community exchange than existing NGSI-LD federation approaches. In non-IID FL experiments, we showcase cross-community enrollment capabilities and expose different DEE coordination trade-offs. Overall, ComDeX enables scalable, adaptive collaboration for data sharing and federated model training.

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Cite This Study

Papadakis et al. (2026) studied this question.

synapsesocial.com/papers/69fbe382164b5133a91a2b0chttps://doi.org/10.1145/3813109
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