Towards an Adaptive Routing Protocol for Low Power and Lossy Networks (RPL) for Reliable and Energy Efficient Communication in the Internet of Underwater Things (IoUT)

Abstract

– Internet of Underwater Things (IoUT) is emerging as a powerful technology to explore underwater things. Reliable communication between underwater things is a significant challenge compared to communication at the surface, notably the unique characteristics imposed by the underwater environment, such as water currents, noisy scenarios, and limited resources. Several routing protocols have been suggested to overcome the challenges in IoUT. The previous works mainly focus either on improving the reliability or energy efficiency of the routing process. Concentrating on both parameters makes the routing process too complex with substantial overhead. Routing techniques face challenges in solving the noise and water current issues in the IoUT environment. The proposed work utilizes the potential of the Routing Protocol for Low Power and Lossy Networks (RPL) on IoUT communication by enhancing its Objective Function (OF) to resolve the routing in the underwater environment. The proposed Underwater Adaptive RPL (UA-RPL) turns the inefficient DODAG construction into an efficient under noisy environment by extending DIO message features. Numerous neighboring nodes receive the extended DIO message, and the nodes that fit into the safety zone are decided according to the multiple routing metrics, such as hop count, ETX, and Energy factor. Entire network traffic is partitioned through multiple parent nodes with the best rank values and attains an energy-balancing routing over underwater things. It helps to improve the network lifetime without compromising communication reliability. The proposed work is evaluated to show its advantages over the underwater environment. The simulation results show that the UA-RPL delivers high performance when varying the underwater things from 15 to 60. Moreover, it outperforms the existing schemes under the IoUT environment.