## 2 Literature Review
### Clustering Heads Selection Protocols  
Clustering routing protocols help enhance a network's lifetime and play a vital role in improving energy efficiency in WSNs. To reach this goal, many researchers have offered papers in terms of clustering head selection approaches. The authors in [8] introduced two combined methods, selecting the ideal CH and establishing a dynamic clustering procedure. Moreover, the proposed protocol employs both types of election procedures (random and periodic) in the same round, with the random method taking precedence at the start of each round/cycle. Furthermore, both the random and periodic election procedures are followed by testing the residual energy to remove the dead nodes and continuing with the remaining nodes in the round regularly. Furthermore, the proposed protocol is well-known for removing dead nodes from the network topology list during the re-clustering process to report black holes and routing latency issues. Finally, the mathematical modelling and analysis of the suggested algorithm are described. In terms of power consumption and network longevity, the experimental findings show that the proposed protocol outperforms the LEACH and FBCFP protocols. In [9], the decision is based on four factors: energy, distance to the center, mobility, and the data queues' length, utilized to simulate an appropriate CH selection. A unique way to tackle this difficulty is presented using the cluster splitting process algorithm (CSP) and the analytical hierarchy process method (AHP). The approach is compared to the base station controlled dynamic clustering protocol (BCDCP) algorithm using four parameters. The simulation results reveal that the proposed strategy for extending network lifetime outperforms the BS-controlled dynamic clustering protocol methodology. The suggested approach reduces energy more than the BCDCP method and has a lower rate of packet loss. In [10], the authors present a cluster-based routing scheme for a heterogeneous (CRSH) network that enables node clustering and data aggregation. The proposed approach selects the most energy-efficient node as the CH based on the node's energy level and accomplishes data combinations to eliminate duplicate data packets. To evaluate its efficiency, the suggested method is simulated in MATLAB and compared to current protocols using numerous performance factors such as network lifetime, energy consumption, and throughput. The data aggregation strategy is used to decrease duplicate data in the network, and the CH aggregates the important information into a single packet and passes it to the BS. The data aggregation approach conserves energy spent on redundant information processing and minimizes network energy consumption; consequently, network lifespan, stability period, and energy expenditure will improve. In [11], the author applies a novel clustering routing topology to raise the LEACH protocol. Selecting the CHs remains as it had been in the original Leach protocol but is based on the high residual energy. Rectangular area regions from the entire network area are applied to the LEACH algorithm, respectively. The mechanism of routing is adjusted in the MAC layer to reduce the congestion and improve the network performance metrics such as throughput, delay, overhead, and average energy through the Network Simulator 2 platform. A better result for homogeneous networks in comparison to LEACH is provided. For selecting cluster heads and non-cluster heads, paper [12] introduces a novel dynamic multipath routing protocol (DMPRP), which is based on a modified particle swarm optimization (M-PSO) algorithm. The best selection of CHs has been taken after calculating the probabilities. Segmenting the network field topology into many groups (clusters) is predicated to get a more efficient energy consumption ratio (ECR) to balance the load and improve performance by selecting the cluster head (CH).