## 2 Previous Work
In case of the sparse network, the gradual power level increase will pose unnecessary communication delay. FBR faces RTS and CTS delay, which is reduced by scheme named Layer by Layer Angle Based Flooding (L2-ABF) [24]. In L2-ABF, the flooding angle of the data packet in a cone shape towards the upper layer (towards the direction of Sink node) is directly adjusted without exchanging RTS-CTS. The power and angle (the length and width of the cone) depend on the layer distance and relative node speed between sender and the receiving nodes, respectively. The protocol minimizes the flooding of the data packets, however, it consumes more energy in the sparse networks because of many attempts to send data in the sparse network with no forwarding candidate in the cone. Additionally, it is not an energy efficient in the dense network environment as well because multiple copies of data packet may be forwarded by different nodes in the cone. The L2-ABF does not use any mechanism to avoid void hole in the underwater environment. In [25], proposed the state-less, location- and receiver-based routing protocol named Directional Flooding-based Routing (DFR). All nodes in DFR knows their own location, location of sink node, and the location their immediate neighbors. DFR does not employ any holding time, which means that all the nodes that receive the copy of a data message will further forward towards upstream. However, DFR controls the flooding direction of the data packets within the certain zone in the direction of Sink node. Size of the flooding zone is adapted with the upstream link quality. As link quality fluctuates in the underwater environment, the flooding zone unnecessarily becomes wider that consumes more energy and reduces delivery ratio. In addition that, void region can still appear in the flooding area and it worsens when the flooding zone decreases due to increase in the link quality of neighboring nodes. However, DFR shrinks the flooding zone upto a point that there should be at least one forwarder in the zone. This can not guarantee the void avoidance in the forwarding zone. In literature, there are different proposals that solely focus on the _sink mobility_ and use depth information to select next hop forwarders to minimize the end-to-end delay, reduce data collection energy cost, and increase packet deliver ratio. Following is the brief discussion of the sink mobility based data collection schemes. Authors in [26], proposed an AUV (which acts as a mobile sink) based distributed data-gathering scheme to efficiently collect data from the selected nodes, called path-nodes, instead of traversing the whole network. The path nodes are the data collection points and are optimally selected to shorten the AUV trajectory as well as achieve network energy efficiency. These nodes are cluster heads and selected during the clustering phase and then they collect data from the member nodes. The AUV collects the data from selected nodes in the trajectory and saves the network energy. However, the cluster formation and deformation pose additional overhead and the communication delay becomes higher if the selected clusters are at long distances. Authors in [27], proposed the AUV-aided underwater routing protocol (AURP) that collects data from multiple points in the network, called gateway nodes. AURP uses controlled mobility to minimize the AUV's mobility path and collects data through heterogeneous acoustic communication channels. This heterogeneous channel enables AUVs to select either short-range high data rate or long-range low data rate channel. AURP saves network energy, however, it fails to minimize energy consumption and data forwarding delay in situation where many nodes are associated to a single gateway and the sparse network scenario, respectively. A mobile geocast or mobicast in the three-dimensional (3D) AUSN with mobile sink has been investigate in [28]. The main objective of the mobicast is to minimize energy consumption and avoid energy hole problem during data collection.