M2M group-based AI routing protocol for IoT networks

Internet of Things (IoT) networks are heterogeneous networks that offer different services depending on their application environment through smart devices (also called nodes). Machine-to-Machine (M2M) routing protocols provide interconnection between nodes. However, IoT and Internet of Everything (IoE) networks are limited to constraints defined by the scenario of the services they implement. For this reason, in this paper, we propose a new routing protocol that uses Artificial intelligence (AI) to interconnect the nodes of an IoT network efficiently. The AI decides the routes based on the tables created by the Publish/Subscribe (Pub/Sub) communication system, relating it to the dataset of features of each device connected in the network (content-based filtering). Consequently, the IoT gateway selects the best node that can provide it without compromising the performance of the network. We performed a routing protocol simulation between the machine that requests resources and who provides them. The proposal is based on a multi-objective optimization technique that uses evolutionary algorithms. The results show that the algorithm selects the most optimal node that can provide the requested resources without any constraint violation and evaluates the most efficient criteria. Consequently, the proposed algorithm can be applied to provide IoT services attending to several constraints derived from the scenarios where the system is implemented.