Fuzzy-Based Deterministic Routing with Probabilistic Flooding in Underwater Acoustic Sensor Networks

With the rapid development of the Internet of Underwater Things (IoUT), Underwater Acoustic Sensor Networks (UASNs) and Autonomous Underwater Vehicles (AUVs) have become key technologies for marine resource exploration, surveillance, and environmental monitoring. However, underwater acoustic channels suffer from low bandwidth, high propagation delay, and high bit error rates, posing significant challenges for efficient data routing. Most hop-count-based routing protocols, though location-free and scalable, often face a tradeoff between end-to-end latency and packet delivery ratio (PDR). To address these challenges, this paper proposes a fuzzy-based deterministic routing protocol with probabilistic flooding (FDPR), a hybrid routing protocol for UASNs with multi-AUVs. Unlike traditional hop-count-based routing protocols (e.g., DVOR and VAPR) that rely on pure flooding, FDPR employs a probabilistic flooding mechanism during the downward broadcast phase to reduce signaling overhead and energy consumption without sacrificing PDR. In contrast to opportunistic routing, where timer-based candidate coordination typically introduces longer transmission delays, FDPR leverages deterministic fuzzy-based relay selection during upward data forwarding. Multiple metrics including hop-count, residual energy, received signal strength, and mobility factor—are evaluated to select the optimal relay, thereby minimizing end-to-end latency efficiently. FDPR integrates probabilistic flooding and fuzzy-based relay selection, achieving reliable packet delivery while reducing both end-to-end latency and energy consumption, providing a practical solution for underwater communication. NS3 simulation results prove that, FDPR reduces the average end-to-end latency by 52.84% and the total energy consumption by 9.84% compared to DVOR, while maintaining a comparable level of packet delivery ratio.