A Scalable Semantic Resource Discovery Architecture for the Internet of Things

Abstract

Resource discovery in the Internet of Things (IoT) provides information about the available sensors, and actuators as well as the services and resources they provide. This task, crucial for IoT applications evolution, allows self-configuration and context awareness. When combined with semantic technologies, resource discovery increases the interoperability and backs the reasoning process. However, introducing semantics into the IoT incurs challenges regarding resources and power consumption as well as the compactness of representations and resource lookup efficiency. In this paper, we discuss such challenges and propose an architecture for including semantics in a scalable IoT system. Next, we present a mechanism aiming to increase semantic resource discovery efficiency in heterogeneous IoT systems. The proposed mechanism is based on the construction of a concept directory to accelerate semantic-based resource lookup. By using such a directory, we take benefits of semantic representations to better match user requests, without lowering discovery task efficiency. The feasibility and effectiveness of our solution was demonstrated by experimental evaluations.