## 3 Related Work  
Currently, great attention has been gained by WSNs in wide applications and research areas, such as industrial, environmental monitoring, and healthcare applications. Due to the limited sensors, communication capabilities between them must avoid the exhaustion of battery energy. To the best of the author's knowledge, the LEACH protocol [15] is the first protocol based on a clustering approach, which uses random selection of cluster heads to distribute the power load equally among network sensors [16]. It also localizes  
Figure 3: Precision agriculture architecture for monitoring application using the multi-hop clustering model in WSNs. Figure 2: Military architecture for monitoring application using the single-hop clustering model in WSNs. coordination to make the dynamic networks much more scalable and robust, and the routing protocol includes a data merging process to reduce the information amount sent to base stations. The results show that LEACH can reduce energy more than eight times as efficiently in comparison with conventional routing protocols. In addition, LEACH can distribute power dissipation evenly across the sensors. However, in the optimum results [17], note the distribution of LEACH's cluster heads is uneven and, in some areas, the cluster heads are very concentrated. There are some areas where there is no distribution of cluster heads. Moreover, some nodes are too far from the cluster heads, which leads to wasting energy in data transmission. In the same way, the FBCFP protocol uses neuro-fuzzy rule-based clustering concepts to perform cluster-based routing [18]. Energy modeling is utilized to perform cluster formation, in WSNs, for efficiently routing packets through the application of machine learning using a convolutional neural network with fuzzy rules for weight adjustment and, hence, the network lifetime is prolonged. However, the focus on the degree of accuracy for choosing the cluster head by performing complex mathematical operations and measuring multiple factors results in delays and drains the network energy that is supposed to be provided. Similarly, DFLER [19] uses fuzzy logic and the ECATCH algorithm to reduce the workload of the cluster head and produce a reliable, accurate results. However, sending all sensor data to a specific CH leads to a bottleneck problem. One strength of NCCM-DC [20] is producing a high-performance protocol to enhance energy efficiency and achieve transmission reliability, but a very high load is produced from the synchronization of multi-hop time. Additionally, FEMCHRP [21] elected the cluster heads using the fuzzy logic and Dijkstra algorithm to perform the data transfer process by selecting the shortest energy path. However, repetitive use of two methods in the CH election process, at each round, leads to significant energy drain. To enhance the total network lifetime and improve the LEACH protocol, a new algorithm was proposed, based on the node rank (NR) algorithm, called NR-LEACH [5]. However, the repetitive calculation for the path cost, and the number of links among the nodes in each round, depleted the NR-LEACH nodes' energy quickly during the CH election process. Another promising approach from Firefly with Cyclic Randomization (FCR) algorithms is proposed in [1], to enhance an effective CH election method considering energy, delay, and distance in WSNs. However, the random method used in cluster head election itself results in great delays due to the black hole problems, and the extended amount of time needed to get out from those holes. It is important to highlight that the work in [22] exploits the transmission range for the control messages and the average number of clusters to prolong the network lifetime effectively. However, repetitive calculations of the transmission range of the control messages and an average number of clusters in each round, causing quick depletion of the network's power, and greatly delaying the operations. Similarly, RTCP [23] exploits the redundant sensors in the same area and clusters them.