# Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility
## 1 Introduction  
Presently, we are in the modern era of information, and almost every field is equipped with technology to stay updated. Underwater wireless sensor networks (UWSNs) are becoming popular due to their advantages, like pollution monitoring, oil extraction monitoring and aquaculture monitoring [1]. These networks consist of a number of wireless sensors (nodes) for specific tasks, such as sensing the physical attributes of the water environment. After sensing the desired information, nodes forward it to the sink. This transmission can be direct or multi-hop, where nodes relay the data of other nodes. In water, acoustic signals are used for communication; these cause a high delay in communication because of their speed (1500 m/s). The reason is radio or optical signals are affected by a huge amount of scattering and absorption loss. Unlike terrestrial WSNs, acoustic channels have high energy consumption, limited bandwidth and low transmission speed, as shown in Table 1[2]. These nodes can bear harsh weather conditions in deep sea and are expected to stay alive on batteries without getting recharged. However, these operate on limited battery power, and it is almost impossible to recharge or replace the batteries. Commonly, sea areas that need to be sensed are large and deep. The underwater deployed nodes have complex transceivers. To limit the interference, nodes are forced to communicate at shortdistances. When the sink is far away, then multi-hop communication schemes are used. The nodes that relay the data of other nodes consume more energy. If a node continuously participates in relaying data of other nodes, it will exhaust its energy, get disconnected from the network and leave the information or an energy hole. Network lifetime (NLT) depends on the lifetime of nodes deployed in the field. To enhance the NLT, efficient management of energy consumption is needed. In UWSNs, different approaches are used for data collection: the autonomous underwater vehicle (AUV) (also named the mobile sink (MS); it can get refueled or recharged periodically; because of this reason, it is assumed that the MS has no constraint with respect to energy) -based schemes use direct or multi-hop communication between the sensor node and the sink [3]; courier node (CN) (these are nodes that are equipped with extra resources) -based schemes for data gathering [4]; and clustering-based schemes to relay the data of member nodes (MNs) [5]. In the first approach, the AUV moves in the field and gathers data from the nodes through multi-hop or direct communication. In the second approach, the CN moves on predefined paths in the network and receives data from nodes at a minimum distance or far away nodes with multi-hop transmission. Like MS, CN also has no constraint with respect to energy consumption. The optimal number of CNs is deployed in the network; otherwise, the cost of the network may increase. In the latter one, a network is logically partitioned into clusters, such that each cluster selects a CH depending on the defined criteria. In [5], after the selection of the CH, CHs further divide clusters into sub-clusters and select a delegate node (path node (PN)) for data gathering. Nodes in the sub-cluster forward their data through the PN, and the PN forwards these data to the sink. Each of the above schemes has advantages and disadvantages. Multi-hop communication minimizes the energy consumption of far away nodes, while nodes that rely on the data of other nodes consume more energy. Furthermore, clustering schemes minimize the energy consumption of MNs; however, CHs have a greater burden. To minimize energy consumption, we propose a three-dimensional sink mobility (3D-SM) scheme. We consider a three-dimensional rectangular network; for simplicity, the network volume is divided into four sub-regions, each called a rectangular cuboid (RC). In one of the RCs, an MS is deployed that gathers data from the nodes present there. The remaining RCs are equipped with CNs that move in, to gather data from the nodes.