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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES)
Mahmood A. Al-Shareeda
Southern Technical University
Economics, Econometrics & Finance

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Heterogeneous internet of things device interoperability using fog-based adaptive semantic mechanism Devamekalai Nagasundaram; Selvakumar Manickam; Mahmood A. Al-Shareeda; Huda Mohammed Alsayednoor; Ali A. Yassin; Shankar Karuppayah
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 3: November 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i3.pp819-836

Abstract

With the rapid growth of heterogeneous internet of things (IoT) ecosystems, insufficient semantic interoperability caused by non-uniform communication protocols, data formats, and semantic representations has become a core challenge in the field. Existing cloud-based, static ontology schemes have defects including high latency, large overhead, and poor adaptability. This paper proposes the dynamic semantic fog (DSF) framework, which performs semantic processing at the fog layer to achieve real-time interoperability. The framework integrates four core modules: workload offloading, resource description framework (RDF) generation, semantic representation, and adaptive ontology expansion. It supports dynamic access to newly added IoT devices. Tests were completed using iFogSim in a smart city traffic scenario. Compared with traditional cloud solutions, the framework reduces latency, energy consumption, and network usage rate by 51.7%, 41.3%, and 55.6% respectively, and can support dynamic semantic interoperability for heterogeneous IoT environments.
A review of intelligent task scheduling models for fog computing in large-scale internet of things networks Sababathy Palanisamy; Erum Ashraf; Selvakumar Manickam; Huda Mohammed Alsayednoor; Mahmood A. Al-Shareeda; Shankar Karuppayah
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 3: November 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i3.pp777-795

Abstract

The rapid growth of internet of things (IoT) applications has generated an urgent demand for efficient task scheduling mechanisms that feature low latency, scalability, and resource awareness. While fog computing can meet this demand by extending computing and storage resources to the vicinity of data sources, it still confronts four core challenges: resource heterogeneity, dynamic workloads, mobility, and security constraints. To address these issues, this study conducts a systematic review of intelligent task scheduling for fog-enabled IoT systems. It classifies the included eligible studies into five scheduling paradigms, and innovatively proposes a cross-domain framework that integrates three types of awareness, including priority awareness. The subsequent work of this study will sort out the core strengths and limitations of existing relevant methods. Finally, open challenges and emerging research directions, including edge artificial intelligence (AI), federated learning, blockchain-assisted scheduling, and hardware-accelerated implementations are discussed. The findings provide useful guidance for developing scalable, secure, and adaptive scheduling frameworks for next-generation fog-enabled IoT systems.
Co-Authors Ali A. Yassin Devamekalai Nagasundaram Erum Ashraf Huda Mohammed Alsayednoor Sababathy Palanisamy Selvakumar Manickam Shankar Karuppayah