# Adaptive Node Clustering Technique for Smart Ocean under Water Sensor Network (SOSNET)
## 2 Related Work  
As with any sensor network, energy preservation is a major goal for UWSN. Many energy efficient routing protocols have been proposed using the depth information. Depth based routing (DBR) [14] is such a scheme that measures the depth of the sensor and based on this information, data from the sensor, which has a lower depth, is sent to the sink nodes. The information of the remaining energy along with depth information is used in energy efficient depth based routing [15]. To mitigate the issue of flooding proposed in DBR, [16] introduces depth based multi-hop routing, which uses multi-hop transmission for reduction of number of packets to be sent to the sink node. Relative distance-based protocol (RDBF) [17] uses a fitness function to decide which node will forward the packet towards the sink. Energy efficient routing protocol (EUROP) [18] introduces a layering concept, which divides the sensor nodes into different layers based on depth information. Delay sensitive depth based routing (DSDBR) [19] is another depth based protocol that uses holding time as a measure to reduce transmission delay. Clustering is a well-known technique used for conservation of energy in sensor networks. Such a scheme is proposed in [20]. In this scheme two- and three-dimension architectures are proposed, which divide the network into two or three clusters, where the cluster head is responsible for communication with the sink node. Dynamic User Coordinate System (DUCS) [21] is a distributed clustering scheme that divides nodes into different clusters; most nodes are limited to communication within the cluster, whereas the cluster head deals with inter-cluster communication. MUD Client Compression Protocol (MCCP) [22] is yet another protocol that selects cluster heads based on the available residual energy, relative position of the node with the sink, and the energy required by the nodes to the candidate node. LCAD (location based clustering algorithm for data gathering) [23] is another such technique developed for three dimensional UWSN. Nodes are deployed in multi-tier fashion and multiple cluster heads are chosen for communication. A review of these techniques is presented in [21; 22; 23]. AI based routing algorithms have gained popularity in many fields of networking. Correspondingly many Ai based routing algorithms have been proposed for UWSN. One such algorithm is Low-Energy Adaptive Clustering Hierarchy (LEACH), LEACH-C [24], which is an enhancement of the LEACH algorithm. The focus of LEACH-C is selection of CH. This process is based on simulated annealing mechanisms that provide an optimal solution for selection of CH with maximum energy levels. Similarly, in [25] the same mechanism, in two rounds, is used for selection of a secondary cluster head, which becomes the cluster head when the energy level of the cluster head falls below a certain threshold. LEACH-SAGA [26] is another enhancement of the LEACH algorithm, which is based on a simulated annealing and genetic algorithm. In LEACH-SAGA the clusters are formed by genetic algorithms and simulated annealing. Then, based on distance from cluster center and residual energy, the cluster head is chosen. Application-Specific Low Power Routing (ASLPR) [27] is yet another routing algorithm that employs simulated annealing techniques for enhancing the lifetime of a cluster head. ASLPR simply selects a cluster head with a high energy value for a specific time period, and after time expires, a new cluster head is selected, again based on the available energy value, to prolong the life of the nodes. Particle swarm optimization (PSO) based techniques are popular for optimization in a variety of computing problems. Similarly, PSO based techniques are available for routing protocols of WSN.