An Ontology-Based Model for In-Network Computing Components Description and Discovery

The increasing demand for ultra-low latency and high bandwidth in emerging applications, such as virtual reality gaming and telesurgery, is challenging current network infrastructures. In-Network Computing (INC) has emerged as a promising solution to these challenges by optimizing network performance, reducing congestion, and minimizing both latency and bandwidth usage. As 6G networks strive to deliver unprecedented connectivity and ultra-low latency, INC is poised to become an integral part of future network architectures. However, a significant gap exists in the literature concerning a comprehensive model for describing INC components, which is crucial for effective INC provisioning. To address this gap, we propose the In-Network Computing Ontology (INCO), a domain-independent, ontology-based model designed to describe and discover INC components in a centralized repository. Our model covers both the functional and non-functional specifications of INC components. Furthermore, we introduce a semantic matchmaking algorithm that uses the INCO model to automatically discover and select the most relevant INC components from the repository based on user requests. Experimental simulations validate our approach, demonstrating the effectiveness of the semantic matchmaking algorithm, particularly regarding response time and consistency.