Ontology-Based Description and Discovery of In-Network Components for 6G Holographic Communication

6G networks aim to enable advanced applications such as Holographic Type Communications (HTC), which demand ultra-high data rates and strict latency bounds. Traditional endpoint-centric architectures fall short in meeting these demands due to inherent latency and scalability limitations. In-Network Computing (INC) addresses these challenges by offloading computation into network elements, which reduces end-to-end delays and improves system efficiency. However, broad INC adoption remains constrained by interoperability barriers, manual configuration overhead, and the lack of semantic descriptions that support automated discovery and reasoning. To address these challenges, we introduce INCO (In-Network Computing Ontology), a semantic framework for describing, discovering, and integrating INC components. INCO captures both functional and non-functional properties, enabling automated matchmaking between application-level constraints and heterogeneous in-network resources. A proof-of-concept implementation targeting live holographic concert streaming, a high-demand HTC use case, demonstrates the effectiveness of INCO. Across 5 representative scenarios, INCO achieves perfect or near-perfect F1 scores, zero false negatives, and over 98 percent precision and recall. It more than doubles the F1 score compared to keyword-based discovery, reduces query latency by more than 60 percent, and maintains sub-3 millisecond response times with per-query memory use below 8 kilobytes. These results show that INCO can automate INC provisioning with high accuracy and improved interoperability across diverse networks and application contexts.