# On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks
## 2 Related Work
A hybrid approach consisting of dynamic and static clustering has been employed in [15]. This technique was developed to overcome the energy holes creation in the network. Authors divide the network into fixed logical regions to avoid the unbalanced energy consumption. Furthermore cluster head selection is done via dynamic and static selection procedures. In [16] authors took multiple pre-existing protocols and proposed their improved versions in terms of delay sensitivity. In order to minimize the end to end delay all the schemes formulates delay-efficient priority factors moreover, enhances the holding time to delay sensitive holding time. While considering the density and node's location a load balancing clustering algorithm has been proposed in [17]. Cluster radius is adaptive in the proposed protocol and adjusts on the basis of nodes density in certain region. Higher the nodes density, lower would be the cluster radius; which has been formulated based on density and nodes' distance with base station. Protocol has been proved to be more stable and enhances the network lifetime as well. In [18], authors consider the node's degree residing in the network. Node's degree is considered as the number of neighbors residing in a certain radius. This node's degree is employed in computation of preferable clustering and relay nodes. The aforementioned protocol is proved to be an energy efficient protocol because higher degree nodes are elected as cluster heads and relays nodes. Therefore, larger number of nodes is accommodated by lesser cluster heads. In [19], an optimization approach EDIT has been proposed that optimizes the two delicate network performance metrics, energy consumption and end to end delay. Two different types of distances between cluster head and member nodes have been considered that defines unique tradeoffs in between energy consumption and delay. Another clustering protocol has been proposed in [20]. In this proposed protocol cluster head is selected through formulating residual energy and the number of neighbors surrounding a node. Moreover, a shortest path algorithm has been employed to obtain a route optimization technique for data forwarding phase. Hence, an energy efficient clustering strategy has been proposed to elongate the network lifetime. In [21] a clustering protocol has been suggested. It performs by distributing the network into fan shaped smaller cells. Furthermore, different energy saving methods have been proposed considering the above mention network layout. Whereas, in [22] LAFR technique has been proposed. In this technique network energy consumption has been cut short by limiting the number of links connected to the upstream node. To prevent data flooding authors employed the routing table being maintained by the downstream nodes. LAFR considers the beam width and three dimensional data transmission by sensors. iAMCTD is a protocol, that has been proposed in [23]. Authors sub divided the acoustic region into three layers. Furthermore, each layer has been assigned with a unique forwarding function. Each forwarding function selects the forwarder node by optimally minimizing the environmental constraints dominant for that specific network layer. In [24], AURP has been proposed that employs multiple AUVs as data relaying nodes. AUVs cut short the transmission distance and aids in efficient data gathering process. AUVs follow a dynamically decided fashion to achieve the maximal network performance in terms of data delivery ratio and energy consumption. SPARCO is a cooperative based routing protocol suggested in [25]. The proposed protocol is a hybrid transmission technique whereas, best relay selection mechanism depends upon the instantaneous path information and distance among neighboring nodes. The protocol has been proposed to lower path loss and improve network stability. Cylindrical networks have been considered in [26] and chain based routing has been employed. This paper proposed multiple schemes elaborating the routing mechanism using 1 to 4 inter-connected chains of sensor nodes.