An AI-based approach for dynamic routing in IoT networks

Dynamic routing problem is an important research challenge for the robust working of the Internet of Things network as many sensors are equipped with limited energy resources. The work carried out in this paper uses a novel energy model to formulate the routing problem for IoT networks. An AI-based approach using a modified A* algorithm proposes a dynamic routing framework for IoT. The simulated results are compared with the k-Means algorithm and genetic algorithm in terms of energy consumption and the number of dead nodes. This comparison reveals the proposed routing framework to outperform than k-Means algorithm and GA by extending the lifetime of the IoT network by a factor of thrice and twice, respectively. Further, the proposed routing framework is also compared over different network configurations.