RACA-MAC: A Routing-Aware and Collision-Avoidance MAC for Distributed Underwater Acoustic Networks

Abstract

Distributed underwater acoustic networks support autonomous coordination and rapid response in complex ocean environments by distributing sensing and decision-making functions to individual nodes. However, under long propagation delays, limited bandwidth, and decentralized scheduling, most existing protocols still struggle to suppress multi-hop conflicts under concurrent multi-flow transmissions while balancing end-to-end delay and energy consumption. To this end, we propose a Routing-Aware Collision-Avoidance MAC (RACA-MAC), which can cooperate with various distributed routing mechanisms. In multi-hop concurrent underwater acoustic networks, relay selection and collision avoidance are strongly coupled. Therefore, RACA-MAC formulates relay selection and transmission timing as a unified relay–timeslot decision problem. Specifically, RACA-MAC constructs a local Flow Competition Graph (FCG) from overheard scheduling announcements, transmission feedback, topology awareness, and flow identifiers to represent spatiotemporal exclusion relationships among multi-hop flows. It then combines routing candidates, seed-based transmission/reception windows, and FCG-based conflict filtering to build a feasible relay–timeslot action set. Based on this set, an absorbing Markov chain models end-to-end forwarding risks under reliability, collision, and energy constraints, while Lagrangian relaxation transforms the coupled constraints into locally computable price-aware cost functions. Consequently, each node dynamically adjusts its relay–timeslot decision under limited local information, enabling end-to-end-performance-oriented distributed multi-hop scheduling. Simulation results show that RACA-MAC improves packet delivery ratio by 20–60%, while reducing end-to-end delay and average energy consumption by up to 30% and 50%, respectively.