# An Energy Efficient Routing Approach for IoT Enabled Underwater WSNs in Smart Cities
## 1 Introduction
This may result in the depletion of nodes where the distance from the sink node is large [24, 25]. The Hop by hop is the second transmission type; where each node senses data and transmits them to the sink by selecting the nearest neighbor as a forwarding node [26]. Consequently, the weight on the nodes increases, which are located closer to the sink nodes and, due to this reason, nodes die early at initial stages. Thereby, the lifetime of a network also decreases. The third one is the most interesting routing protocol to the researchers, known as clustering based routing [27]. Every sensing node underwater transmits the gathered data to its corresponding Cluster Heads (CHs) and, after that, every CH conveys its aggregated data to the BS [28]. In such a way, node to node exhaustive transmission is minimized, bandwidth consumption is reduced and network lifetime increased [29]. Therefore, the implementation of routing protocol is an emerging research area for IoT-UWSN to provision the smart city idea. For the evaluation of our work presented here, we have considered three different node to BS scenarios. The cases are as follows. In the first scenario, single sink node is placed at the surface of the water. In the second scenario, four sink nodes are positioned at an equal distance from one another at the water surface, while, in the third scenario, two sink nodes are deployed; one node is placed at the water surface, whereas the other one is positioned inside the predefined 3-D region. The motivation behind considering these scenarios is to discover one of the best routing protocol, which performs effectively and efficiently in a particular scenario. As we know that, in the practical world, we may face several constraints due to which we may need to deploy nodes differently. For this reason, we have considered the aforementioned scenarios and, according to these scenarios, the research work presented here shows that DEEC-(ACH)\({}^{2}\) algorithm generates desired results in most of the cases, especially in terms of the number of packets sent to BS and the number of packets received at BS. TEEN-(ACH)\({}^{2}\) protocols perform best for exhibiting less packet drop ratio. The proposed scheme aims to examine the terrestrial based routing protocols' performance in the underwater environment. In the proposed scheme, the nodes are arbitrarily located in the predetermined region, whereas sink(s) are either placed at the top of the water surface or either placed at two alternate positions. The sink one inside water while the second one at the water surface. After nodes deployment, every node newscat a HELLO packet for the sake of receiving an acknowledgment of its resources from the neighbors. The selection of CH is a challenging task, as it directly influences the performance of the network. The most ideal node ought to be identified in order to prolong stability period of a network lifetime. The selection of CH is constrained by a number of parameters, such as the energy level of the node, the lossless transmission of data packet to the BS, and delivery of the data packet by the sensor node. Nevertheless, if CH is located in a dense area where its cluster members also exist in high range. CHs are also re-elected after each round. The energy of CH is utilized and depleted for the transmission of data packets to BS. In the case when the residual energy of a particular node does not satisfy the threshold level of a node selection of the CH, then the sensor node transmits the data packet of that node to the BS. The network stability is badly affected due to such a situation. The above listed reasons make the CH selection a challenging endeavor [30]. In the proposed study, each node evolves into a CH for a particular round if the remaining energy is exceeding the averagely computed remaining energy of the concerned network. However, in this way the selected CHs are not ideal in count, due to which different sizes of clusters are created. By having so, the load on these unbalanced clusters becomes high.