# An Energy Efficient Routing Approach for IoT Enabled Underwater WSNs in Smart Cities
## 2 Literature Review
### Cluster-1 Protocols Holding Homogeneous Energy  
In [32], Depth-based Routing (DBR), a depth based proactive routing protocol, is proposed, where multiple data packets are forwarded hop by hop, depending upon depth difference. DBR shows that its stability period is very poor, as low-depth nodes die in the very initial stages. Because of multi-hop, energy consumption while data transmission increases and, thus, the lifetime if a network decreases [33; 34; 35]. Extended forms of DBR are EEDBR [36; 37], and CDBR [38] were proposed, where the network's lifespan is increased by limiting the number of forwarding nodes. These nodes are nominated, depending upon the depth as well as residual energy, which prolongs the lifetime of nodes. However, in the dense network, these protocols do not perform well as the load on medium depth nodes increases. Hence, these kinds of nodes die sharply at initial stages. A homogeneous proactive routing protocol namely CoDBR is proposed in [39], in which relay nodes are nominated, depending upon the depth. The relay nodes that are selected forwards the data packets cooperatively to the sink node. By considering cooperative routing at the network layer, the throughput and reliability of the network increases. However, the redundant transmission of similar data packet occurs due to which high energy is consumed. Like DBR, it also neglects residual energy and link condition and, besides these shortcomings at a very initial level, nodes having low depth die because of fixed depth threshold \(d_{th}\)[40]. In [41], the authors proposed a Reliable and Energy efficient Pressure-Based Routing (RE-PBR) protocol for UWSNs. RE-PBR considers three factors, including join quality, depth, and remaining energy for adjusting energy utilization and solid information conveyance. In particular, the quality is assessed by utilizing the triangle metric technique. A lightweight data obtaining algorithm is created for productive information revelation of the system. Multi-metric data sending calculation is planned dependent on course cost estimation, which uses leftover energy and connection quality. Simulations were performed in NS-2 with Aqua-Sim to assess the exhibition of RE-PBR. The proposed protocol is equated with the DBR and EEDBR. According to the authors, RE-PBR performs better in the case of end to end delay, energy utilization, and network lifetime range. However, the limitation of this technique is the consumption of long time duration. The authors of improved Adaptive Mobility of Courier nodes in Threshold-optimized DBR (iAMCTD) [42; 43], proposed a Forwarding-Function (\(F_{F}\)) based routing protocol for time-sensitive applications in which not only depth and residual energy are considered. Moreover, it deals with the Signal to Noise Ratio (SNR) as well. To reduce the transmission loss, an optimal Holding Time (\(H_{r}\)) is calculated that ultimately enhances network lifetime. The depth threshold varies following the density of a network, which requires network information on a regular interval basis. Due to this variation, a list of eligible neighbors increases and causes a reduction in critical data deficits and end to end delay. Mobile sinks are considered in a cooperative based routing protocol, named as Depth and Energy Aware Dominating Set (DEADS) [44]. The protocol considers three stages while performing. During the first stage, neighbors are selected. Domain Set (DS) and Cooperative Courier (CC) are selected from neighbors while the second stage. Afterwards, data are sensed and forwarded to the sink depending upon the threshold value in the data forwarding phase. Improved throughput and decline in packet drop value is gained in exchange of high energy depletion. In Adaptive Cooperation in EEDBR for UWSN (ACE) [45; 46], single and double re-transmission the procedure is utilized in order to expand the throughput. The maximum number of nodes joined in retransmission progression results in maximum sets of packets collected at the sink.