## 4 Related Work  
In this section, we will provide a brief overview of the most important works that have proposed extensions or improvements to the basic LEACH protocol discussed in the previous section. In [19], the authors proposed an effective differential evolution (DE) based routing algorithm, named DE-LEACH, to improve the performance of LEACH. DE-LEACH's CHs selection process is similar to LEACH, i.e., random selection based on threshold value shown in Equation (8). DE-LEACH is designed by leveraging two of the most important factors of WSNs, which are energy consumption and the distance separating neighboring nodes inside a cluster, to overcome the early death of CHs issue. DE-LEACH features a fast search mechanism based on optimum level while selecting CHs in the setup phase. Performance evaluation results, using simulation, show that DE-LEACH can successfully prevent random selection of nodes during the clustering process while improving large-scale WSNs lifetime. However, the exclusion of random selection of CHs using optimal level based on residual energy increases the complexity of the algorithm and the overhead in the network [19]. In Energy-Efficient LEACH (EE-LEACH) protocol, proposed in [20], the CH selection is based on the residual energy where a sorting algorithm extracts the residual energy of each sensor node and the one which has the maximum residual will be chosen as a CH. Gaussian distribution is used for computing the coverage probability. The collection of data can save substantial energy despite the fact that one cluster formed in a small area can consume less energy than the cluster formed in a larger one. The experimental evaluation of EE-LEACH highlights that it has higher packet delivery ratio, lower end-to-end delay and lower energy consumption, but It achieves this at the cost of more traffic on the network. In Intra Cluster Balanced Cluster LEACH (IB-LEACH Protocol) [21], the clustering process is divided into two phases, i.e., intra cluster and inter cluster, which will further help to increase the energy efficiency of the system. The evaluation results reveal that the use of  
Figure 2: LEACH frame operation. IB-LEACH protocol increases the network lifetime. On the other hand, due to the extra computing required it increases the traffic load to some extent. Assisted LEACH (A-LEACH) [22] is an amplified form of LEACH aiming to minimize the power dissipation of CHs by introducing a helper node, called assistant node, to the cluster head. In A-LEACH, when a cluster is formed and the CH is selected this latter selects a helper node located near the base station. Then, the cluster head aggregates the received data from the cluster members and sends it, through the selected helper node, to the BS. The evaluation results has shown that A-LEACH performs better than LEACH. Balanced-LEACH (LEACH-B) uses de-centralized approach for cluster formation in which each node knows the final destination to transmit data to and its own position but has no information about other nodes [23]. LEACH-B operation consists of three steps, cluster formation, CH selection and data transmission. A sensor node sends data to destination node using the best path characterized by the low power dissipation and based on that it selects the CH. Firstly, the great convergence and global optimization capability of the proposed algorithm can reasonably divide the entire network area into a number of sub-regions. Then, in each sub-region a CH is elected taking the residual energy factor into account. The conducted experiments results have shown that, compared to LEACH, LEACH-B can effectively balance the network load and improve the energy usage, so as to extend the network lifetime. However, the division of the entire network into sub-regions increases the communication overhead in WSNs [23]. In Round Robin Cluster Head (RRCH) [24], clusters are created one time only, using similar method to LEACH, in order to minimize the energy usage during the clustering phase.