# Path Diversity Improved Opportunistic Routing for Underwater Sensor Networks
## 1 Introduction  
Underwater sensor networks (UWSNs) have attracted strong attention from both researchers and industry in fields such as oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, marine fish farms, etc. [1; 2; 3; 4]. UWSNs are a new research paradigm that poses exciting challenges compared to the ground-based existing networks due to the intrinsic properties of underwater environments [5]. The pre-defined routing protocols cannot be applied to UWSNs successfully because the characteristics of the underwater acoustic physical channel, including limited bandwidth, high propagation delay, high bit error rate (BER) and temporary loss of connectivity, may result in high energy consumption and weak reliability. When packets are transmitted along the pre-defined route, once a partial communication link is shut down, the entire path will be unreachable. Comparing traditional routing protocols, opportunistic routing (OR) has been proven as a promising paradigm to design routing protocols for UWSNs [6]. The main idea of OR is shown in Figure 1. When a sensor has packets to deliver, instead of a unique next-hop forwarder in traditional multi-hop routing, OR selects a set of next-hop candidate nodes on the fly at each hop to forwardpackets. OR can combat packet losses by taking advantage of simultaneous packet reception among the candidate set. Then, the packets will be forwarded in a prioritized way towards the destination [7]. Candidate set selection plays a significant role in OR protocols. It handles selecting a subset of neighboring nodes to continue to forward the packet toward the destination [6]. Candidate selection methods in existing works can be divided into three categories: geographic-based [8; 9; 10; 11; 12], depth-based [9; 13] and EPA-based [14; 15; 16]. Geographic-based methods take advantage of node's location to forward packets. It can limit the forwarding direction and the forwarding range to save energy (e.g., VBF [9] and HH-VBF [10]). They use the ideal assumption that the geographical information of nodes can be obtained easily. Actually, finding the location information of nodes is the primary challenge as global positioning system (GPS) waves in the 1.5 GHz band do not propagate through water. Further, fine-grained localization by underwater positioning techniques with limited energy expenditure is difficult [17]. Depth-based methods always take the depth information to make routing decision locally. It does not require topology or route information. Without effective retransmission suppression, the depth-based selection method applied in DBR protocol [13] results in too much retransmission. That is not suitable for UWSNs due to the higher energy consumption. The EPA-based methods employ the forwarding progress and underwater fading channel to chose forwarding nodes. The EPA (Expected Packet Advance) metric [18] is defined as packet forwarding advancements provided by the neighboring nodes. In Hydrocast [14], a heuristic algorithm is proposed to find a neighboring set with the maximum normalized sum of advancements to forward packets. Although the EPA-based method can provide good solutions to against the underwater unreliable communication channel, a major issue is ignoring the effect of candidates location distribution and candidate set size on path reliability. The routing void problem poses a challenge to OR protocols. It occurs whenever the current forwarders have no neighbor node closer to the destination than itself. There are various reasons for the presence of void areas, such as sparse topology, temporary obstacles, unreliable nodes or links, etc. [16]. Many void-handling techniques for routing protocols have been proposed in UWSNs [19]. Several techniques, such as flooding techniques, backward forwarding, transmission power adjustment, network topology control, etc., are proposed to recover path when the forwarder located at the local maximum point.