Exploiting Semantic-based Thing Equivalence in a QoS-aware M2M Fog Platform

The Internet of Things (IoT) envisions billions of sensors seamless connected to information systems, providing a sensing platform for applications. The large number of smart objects integrated together will offer an abundance of sensors collecting overlapping data or providing similar functionalities. In this scenario, efficient search and appropriate selection of things through proper context acquisition and management will represent a critical requirement and a challenge for future IoT platforms. In this paper, we present the practical approach adopted in the BETaaS platform to model and manage context, and how this information is exploited to implement QoS-aware things selection. In particular, it is shown how context can be used to infer knowledge on the equivalence of things through semantic reasoning, and how such information is exploited to implement an efficient management of things that enforces QoS requirements. The proposed approach is validated through experiments that demonstrate how the proposed solution is effective in detecting things offering overlapping services, and how this can be exploited to ensure service continuity.