# A Two-Stage Routing Protocol for Partitioned Underwater Wireless Sensor Networks
## 2 Literature Review  
In [14], the authors propose a three-stage routing protocol aiming at tackling the energy hole minimization problem. In stage 1, nodes are deployed in circular regions around a sink node termed corona. Each corona region has equal width and the nodes deployed in a particular corona are equidistant from the sink node. In stage 2, load weights are calculated for every corona. Transmission ranges of nodes in a particular corona correspond to the load weight of that corona. This helps in achieving balanced energy dissipation. Stage 3 executes actual data transfer based on the predetermined topological setting and load weights. This scheme successfully reduces energy holes in the coronas near the sink node for fixed networks with predetermined topologies. However, in case of mobile networks where topology cannot be predetermined, the performance of this scheme may be seriously compromised. In [15], the authors propose a cluster based routing protocol. Nodes are deployed in layers in such a way that the layers nearer to the sink nodes have smaller widths compared to the farther layers. The aim of this layering structure is to reduce the chances of creating hot spots by adjusting the transmission powers of nodes based on their distance from the sink node. Furthermore, nodes are grouped into clusters within each layer. Clusterhead for each cluster is selected based on its neighborhood connectivity, residual energy and its distance from the sink node. Data transmission begins once the clusters are formed. Relay selection is based on residual energy and distance of the candidate relay from the sink node. This scheme reduces chances of the early death of nodes due to energy drainage by reducing contention. The reduction in contention is achieved by setting contending radii of clusterheads according to their distance from sink. In [16], the authors propose a cluster-based protocol for data collection. Nodes are positioned in hexagonal style and are grouped into a cluster. Cluster heads are selected based on the position of the nodes within the cluster and their residual energy levels. That is, the nodes that are located near the center of the cluster and have highest residual energy are the best candidate for selection as cluster heads. For data collection, [17] uses an Autonomous Underwater Vehicle (AUV) that uses ant colony optimization to determine shortest paths for its traversal in order to reduce end-to-end delays. The proposed scheme reduces end-to-end delays, and improves network lifetime through better energy management. In [17], the authors propose a two-stage, depth-based routing scheme. In phase 1, called the update phase, nodes share information such as residual energy, node type, etc., with their neighboring nodes. This helps populate neighborhood tables of the nodes which are used to make forwarding decisions during the second phase, i.e., the routing phase. In the routing phase, void regions are avoided by proactive identification of such areas. As the process is carried out locally, it does not incur extensive communication overhead. The packet delivery ratio is improved by regulating the forwarding area according to the node density of the area ahead. In [18], the authors propose a two-stage, multi-sink routing scheme. In stage 1, called the layering stage, nodes are deployed in concentric layered structure around each sink node thus forming a structure in which a particular node may be located in the layered structure of more than one node. The layers are refreshed if the packet delivery ratio (PDR) drops below a certain PDR threshold value. The layering stage is followed by the communication stage which selects an appropriate sink node for each node and also establishes and efficient path towards that sink. The criteria for route establishment aims at improving PDR and energy efficiency. The shortcoming of this protocol is the lack of mechanisms to handle connectivity holes.