A Mobile Matchmaker for Resource Discovery in the Ubiquitous Semantic Web

Abstract

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT), joining semantic-based intelligence and pervasiveness. Existing Semantic Web reasoners are currently impractical for SWoT, as they are resource consuming and optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick resource discovery and decision support through semantic matchmaking in low CPU/memory and battery-powered devices. This paper presents a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, a case study is presented in the ubiquitous Semantic Web and a performance evaluation is provided on a smartphone testbed.