IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v17y2025i4p140-d1619630.html
   My bibliography  Save this article

Enhancing IoT Scalability and Interoperability Through Ontology Alignment and FedProx

Author

Listed:
  • Chaimae Kanzouai

    (LSATE Laboratory, National School of Applied Sciences, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco)

  • Soukaina Bouarourou

    (Faculty of Sciences, University Mohamed V, Rabat 10090, Morocco)

  • Abderrahim Zannou

    (ERCI2A, Faculty of Science and Technology Al Hoceima, Abdelmalek Essaadi University, Tetouan 93000, Morocco)

  • Abdelhak Boulaalam

    (LSATE Laboratory, National School of Applied Sciences, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco)

  • El Habib Nfaoui

    (L3IA Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco)

Abstract

The rapid expansion of IoT devices has introduced major challenges in ensuring data interoperability, enabling real-time processing, and achieving scalability, especially in decentralized edge computing environments. In this paper, an advanced framework of FedProx with ontology-driven data standardization is proposed, which can meet such challenges comprehensively. On the one hand, it can guarantee semantic consistency across different kinds of IoT devices using unified ontology, so that data from multiple sources could be seamlessly integrated; on the other hand, it solves the non-IID issues of data and limited resources in edge servers by FedProx. Experimental findings indicate that FedProx outperforms FedAvg, with a remarkable accuracy level of 89.4%, having higher convergence rates, and attaining a 30% saving on communication overhead through gradient compression. In addition, the ontology alignment procedure yielded a 95% success rate, thereby ensuring uniform data preprocessing across domains, including traffic monitoring and parking management. The model demonstrates outstanding scalability and flexibility to new devices, while maintaining high performance during ontology evolution. These findings highlight its great potential for deployment in smart cities, environmental monitoring, and other IoT-based ecosystems, thereby enabling the creation of more efficient and integrated solutions in these areas.

Suggested Citation

  • Chaimae Kanzouai & Soukaina Bouarourou & Abderrahim Zannou & Abdelhak Boulaalam & El Habib Nfaoui, 2025. "Enhancing IoT Scalability and Interoperability Through Ontology Alignment and FedProx," Future Internet, MDPI, vol. 17(4), pages 1-20, March.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:4:p:140-:d:1619630
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/17/4/140/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/17/4/140/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:17:y:2025:i:4:p:140-:d:1619630. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.