Knowledge Representation-Based Resource Matching Method for Unmanned Surface Vehicle

In traditional unmanned surface vehicle operations, cloud collaboration methods based on cloud service architecture virtualize all operational resources of unmanned platforms for registration and unified management in the cloud. Resources are dynamically provided to requesters through service discovery. However, traditional service matching algorithms fail to flexibly allocate platform resources and facilitate efficient collaboration between different unmanned platforms. This paper explores the cloud service discovery process for unmanned surface vehicles and designs a matching method for cloud service functional attributes based on an ontology knowledge representation model. Through an example of the cloud service discovery process, the feasibility of this method is verified. It enables flexible registration and management of shipborne sensor, communication, and weapon resources, providing a path for quick and accurate cloud service discovery among unmanned surface vehicles.