Heterogeneous internet of things device interoperability using fog-based adaptive semantic mechanism

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. This study proposes DSF, which 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.