## 1 Introduction  
Underwater sensor networks (UWSNs) have received increasing attention from researchers as a core technology enabling applications such as ocean environmental monitoring, resource exploration, and disaster warning. However, the environments in which they operate present numerous challenges, including high propagation delays, limited bandwidth, constrained energy resources, and unstable node positions. These challenges make it difficult to directly apply routing protocols from terrestrial or aerial networks [1, 2]. In practical deployments, nodes often experience random drifting due to ocean currents and encounter difficulties in replenishing their energy supplies, which further exacerbates the uncertainty and instability of routing decisions [3, 4]. Therefore, designing a routing protocol that balances local and global awareness and offers high energy efficiency and reliability is essential for improving the performance of underwater networks. To address these issues, this paper proposes a routing strategy that integrates a dual-layer weight adjustment mechanism at the node and network levels. By adopting a cross-layer design approach, it incorporates physical-layer information, such as received signal strength and link stability assessment, to provide dynamic criteria for relay node selection. The system uses a non-clustered, hop-by-hop data forwarding scheme and leverages surface buoy nodes as supernodes for global coordination. This mitigates performance bottlenecks caused by node drift and uneven energy consumption, thereby improving the reliability and lifespan of data transmission across the network. Due to the random drift of some nodes caused by ocean currents and the high cost of maintaining clusters, this paper adopts a non-clustered, hop-by-hop communication model. Relay nodes perform leap-based forwarding, while surface buoys serve as supernodes responsible for global broadcasting and data collection. Buoy nodes can store the collected information and transmit it to unmanned aerial vehicles (UAVs). This research incorporates cross-layer information from the physical layer into the network layer. Nodes use the real-time received signal strength (RSS) obtained at the physical layer as a local evaluation metric and dynamically integrate it into the relay node selection strategy at the network layer. Additionally, during data forwarding, nodes use power control at the physical layer to select appropriate transmission power levelsto prevent resource waste. The nodes also iteratively calculate a Link Energy Stability Factor to assess the long-term stability of the communication paths from a global perspective. This joint routing decision mechanism, which combines local link quality and global network stability, significantly improves the reliability of data transmission and reduces the retransmissions and control overhead caused by unstable paths, thereby enhancing the overall energy efficiency of the network. To address the hotspot problem, this paper adopts a layered random node deployment strategy. Considering the high data traffic around the sink nodes, the network is designed to randomly deploy more nodes in regions closer to the sink. This deployment strategy effectively mitigates hotspot issues and reduces routing voids caused by local node energy depletion, thereby enhancing network stability and reliability. Moreover, the randomized distribution avoids excessive node concentration or sparsity, helping to balance the load and further extend the network lifetime. A mechanism for dynamically adjusting the reception range is also introduced, enabling nodes to handle directional data flows more efficiently, optimize relay node selection, reduce redundant forwarding, and alleviate communication congestion. To further reduce the communication overhead, this paper implements a dynamic power adjustment and listening mechanism. The traditional ACK mechanism is avoided during data forwarding.