  Effective data routing is vital in the Internet of Things (IoT) paradigm,
especially in underwater mobile sensor networks where inefficiency can lead to
significant resource consumption. This article presents an innovative method
designed to enhance network performance and reduce resource usage, while also
accurately determining component weights in these networks, ensuring quality
service. Building upon previous research on multi-criteria decision-making
systems in coastal RPL networks, our method involves key adaptations for
underwater environments. It integrates comprehensive network features to
identify the optimal parent node for each sensor, employing the fuzzy SWARA
decision-making approach under uncertain conditions. This method takes into
account various factors including hops, energy, ARSSI rate, delay, ETX, link
delivery rate, and depth to determine the most effective parent node
assignment. Through simulation, our approach demonstrates marked improvements
in network performance compared to existing solutions. These advancements are
significant, offering a new direction in enhancing underwater IoT
communications and suggesting wider applications for IoT systems facing similar
challenges.
