Enhancing Semantic Discovery in oneM2M with Direct Query

Abstract

Semantic information has been proven to be necessary in order to increase IoT interoperability by adding meaningful annotations to the data under exchange. The oneM2M as a global standard for IoT middleware has already supported semantic capabilities and allows semantic information to be annotated in its resources. Based on the added semantic information, oneM2M can support more effective resource discovery with semantic discovery. However, the oneM2M approach for semantic discovery is based on indirect query that requires pre-collection of all semantic information distributed in the resource tree while performing the discovery, thus results in very slow response. In this research, we propose a method of direct query to expedite the function of semantic discovery in oneM2M. In our approach, instead of storing the semantic information in the resource tree, we store the semantic information separately and centrally in a permanent RDF store. Our method significantly reduces the response time when performing semantic querying.