## 2 Materials and Methods
### LEACH (Low-Energy Adaptive Clustering Hierarchy)
#### 2.3.1 Enhancements of LEACH  
There are several drawbacks with LEACH. The setup phase is non-deterministic due to randomness. It may be unstable during setup phase that depending on the density of sensor nodes. It is not applicable on large networks as it uses single hop for communication. CH, which is located far from BS, will consume huge amount of energy. It does not guarantee the good CH distribution and it involves assumption of uniform energy consumption of CH during setup phase. And also, the main problems with LEACH lie in the random selection of CH. Various studies have been conducted to improve the LEACH protocol to improve network lifetime, energy savings, and performance and stability [21; 22; 23; 24; 25; 26; 27; 28]. LEACH-Centralized (LEACH-C) method was developed for improving the lifetime of the network in the setting stage and also each node transmits information related to the location and energy level to the BS. The BS determines the cluster, as well as the CH and each cluster node. Through this, it was possible to extend the life of the network and improve energy savings [21]. In addition, in S-LEACH, solar power is used to improve WSN life. Typically, the remained energy is maximized to select a node with redundant power, and the node transmits the solar state to the BS along with its energy level. As a mechanism, nodes with higher energy are selected as CH, and the higher the number of recognition nodes, the better the performance of the sensor network. According to a Simulation results, S-LEACH significantly extends the lifetime of WSNs [23]. In addition, in the case of a LEACH, a new node concept that reduces and provides a uniform distribution of dissipated energy by dividing routing work and data aggregation, and supports CH in multi-hop routing is introduced. Energy-efficient multi-hop pathways are established for nodes to reach the BS to extend the life of the entire network and minimize energy dissipation [28]. As a method for saving energy, H-LEACH was developed with various algorithms that consider the concept of minimizing the distance between data [21]. It adds a CH of LEACH to act as the Master Cluster Head (MCH) to pass the data to the BS. In addition, it is proposed I-LEACH to save energy, while communicating within the network. In order to increase the stability of the network, we proposed Optimized-LEACH(O-LEACH), which optimizes CH selection [29]. This means that the selected CH is based only on the remaining dynamic energy. If the energy of the node is greater than 10% of the minimum residual energy, the node is selected as CH, otherwise the existing CH is maintained. In order to deal with situations in which the diameter of the network increases beyond certain limits, D-LEACH randomly places nodes with a high probability of being located close to each other, called twin nodes. It is necessary to keep one node asleep until the energy of another node depletes. Therefore, D-LEACH has uniform distribution of CH so that it does not run out of energy when longer distance transmission takes place [21]. The D-LEACH method ensures that the selected cluster heads are distributed to the network. Therefore, it is unlikely that all cluster heads will be concentrated in one part of the network [25].