Searching the social Internet of Things by exploiting object similarity

One of the major issues of Internet of Things (IoT) is discovering which objects are able to execute specific services and provide the required data for applications to be correctly accomplished. In recent years, the Social IoT (SIoT) paradigm, where objects establish social-like relationships, has become popular as it presents several interesting features to improve network navigability and implement efficient discovery methods. This is due to the intrinsic capability of a SIoT network to come to a solution for a query and quickly reach the required object with a small number of hops, using object friendships. In this paper, a SIoT-based object discovery mechanism is proposed. The novelty of this algorithm is that the next hop to query is chosen based on two properties: one that is intrinsic to the network and is based on object friendships, and an external one that takes into account the similarity between the object and the query. Simulation results prove that a correct balance between the two introduced properties is needed and that the proposed algorithm is able to efficiently solve queries, independently of their popularity and complexity.