###### Abstract
[17] discussed candidate node set selection and candidate node coordination procedure in opportunistic routing and provided detailed guidance for opportunistic routing design in underwater sensor networks. [PERSON] et al. [18] proposed a reliable path selection and opportunistic routing protocol, named RPSOR, for underwater WSNs. RPSOR guarantees reliability by adding information from the next forward region to the priority function, thereby reducing network energy voids and reducing packet loss rate. [PERSON] et al. [20] proposed a cluster-based adaptive routing algorithm (CBAR) for large-scale underwater WSNs, which simplifies the format of the transmission data packets to adapt to the clustered network structure. Furthermore, CBAR uses dynamic routing updates to adapt to the specificity of the underwater environment and utilizes power control to diminish routing energy consumption. [PERSON] et al. [26] proposed an opportunistic routing protocol (ROEVA) based on reinforcement learning for underwater acoustic sensor networks, which improves the reliability of data transmission while extending the network lifecycle and solving the routing holes problem. All in all, the research on terrestrial WSNs routing technology has become more and more mature, and the research on underwater WSNs routing protocol has gradually deepened. However, the MSR nodes are sparsely deployed on the sea surface and move frequently, the network topology changes dynamically, the delay is high, and there is no end-to-end continuous connection. It has the characteristics of a delay-tolerant and fault-tolerant network, which brings great difficulties to the design of MSR-WSNs routing protocol. In addition, opportunistic routing face two main challenges in MSR-WSNs: (1) the problem of packet duplication under time-varying topology; (2) the waiting-time problem of the sending node under uncertain sea conditions. Simultaneously, real-time updating of routing metrics among marine nodes will yield high communication costs in MSR-WSNs [4]. The comparison of the proposed opportunistic routing protocol and benchmark routing protocols is shown in Table 1.  
Aiming at the problem of the instability in marine communication links, this paper first proposes an effective link reliability prediction method to quantify the connectivity between nodes. Next, we choose the candidate nodes whose geographic progress exceeds the threshold \(\theta\). We find the optimal \(\theta\) by computing the minimization of the expected total delay of forwarding a MSR data packet from the farthest node to the sink. By combining network connectivity with geographic progress threshold, the optimal expected packet advancement that balances hop count and network link quality is derived to gain optimal end-to-end performance. Moreover, by considering the extreme movement of nodes, we calculated the minimum time to maintain link connectivity and set it as the node waiting time, thereby further reducing network delay. Subsequently, the priority of candidate nodes is calculated based on the four metrics, elaborated in the Section 3. Finally, after sorting the priority of the candidate nodes in descending order, the marine data packet forwarding is completed using timer-based coordination algorithm. The main contributions of the present work can be summarized as follows:  
1. We consider the situation where all marine nodes move in real-time, which is in line with the real scenario of maritime search and rescue. 2. A novel link connectivity metric function is proposed to predict the reliability of marine communication links, and combined with the minimum time for maintaining direct link connectivity between nodes to ensure the stability of MSR-WSNs. 3. We propose a novel candidate nodes priority calculation technique based on the link connectivity between marine nodes, the optimal expected packet advancement prediction, the distance from the sensing nodes to the sink, and the remaining energy distribution of the nodes.