A Centralized Service Discovery Algorithm via Multi-Stage Semantic Service Matching in Internet of Things

In recent years, the number of services in Internet of Things (IoT) has increased rapidly, and service discovery in IoT has become more difficult in large-scale registration. In the traditional matching method, in order to get a better match results, all the matching parameters for services had to be calculated together, thus it would waste a lot of computing resource and time. This paper presents a service discovery algorithm via multi-stage semantic service matching algorithm. It adopts the method of layer filters, considering the various constraint parameters of IoT services, such as service category, input/output (IO), precondition/effect (PE) and quality of experience (QoE). It can obtain the proper matching results in a more efficient way. Firstly, we use IoT service description language OWL-Siot to describe IoT services and request uniformly. Then, we propose a four-layer structure model for service discovery, namely interactive interface layer, parsing annotation layer, service matching layer and data semantic layer. We also propose a hybrid service matching degree measurement by synthetically calculating the concept logic and semantic similarity for each layer separately. Experimental results show that the method can effectively improve the performance of service discovery.