## 3 Proposed Methodology
### Clustering Management  
The LEACH protocol increases power efficiency in WSNs by implementing CH_Rotations selection in each loop. However, the standard LEACH has various limitations regarding random CH selection, CH location relative to AP consideration, CH location relative to its ordinary nodes location, the number of ordinary nodes in each CH, and the number of CHs in each loop [38]. Therefore, we update the LEACH protocol to enhance its performance, as the distance between WSN nodes themselves and between them and the AP has a strong effect on power consumption during the communication process. The average distance between neighbour WSN nodes (\(\beta\)), the closest distance (\(d\)) to the AP, and the WSN node energy (\(E\)) are considered along with the LEACH parameters in the establishment phase to select the most suitable CH. Moreover, a new CH node can be selected in advance for the next loop, unlike in the standard protocol. The steady-state will be the same as the standard LEACH protocol. These alteration processes are depicted as follows:  
1. Our work's computing radio energy (\(E\)) model is based on [60] for each WSN node. The primary source of power usage is correspondence between WSN nodes, so power consumption is proportional to the distance between the transmitter and the receiver. The transmitter consumes power to operate the electrical transmission circuit and amplification, while the receiver consumes power to operate the cellular electronics of this embodiment. The power law of the distance between the transmitter and receiver can be used to shape the propagation of electromagnetic waves. As a result, the transmitter circuit uses \(\mathrm{P_{TX-elec}}\) in proportion to the message transmitting size (\(q\)-bit) in terms of distance (\(d\)). The transmitter uses \(\mathrm{P_{TX-amp}}\) to amplify the signal in order to produce a reasonable signal-to-noise ratio. The radio model's cumulative power spent to transmit \(q\)-bit over distance \(d\)(\(\mathrm{P_{TX}}\)) is proposed to be (2): \[\mathrm{P_{TX}}(q,d)=\mathrm{P_{TX-elec}}(q)*\mathrm{P_{TX-amp}}(q,d)\] (2) where \(\mathrm{P_{TX-amp}}\) is equivalent to either \(\beta_{\mathrm{fsm}}\) in a free space model or to \(\beta_{\mathrm{trm}}\) in two-ray ground propagation models depending on distance between transmitter and receiver. Furthermore, a WSN node is in charge of transmitting data messages to other WSN nodes. As a consequence, WSN nodes will accept messages from other  
Figure 2: The structure of the general proposal model. WSN nodes. Equation (3) can be used to measure the power needed to receive the \(q\)-bit message \(\mathrm{E_{RX}}\): \[\mathrm{E_{RX}}(q)=\mathrm{E_{RX-elec}}(q)=\mathrm{E_{elec}}\times q\] (3) where \(\mathrm{E_{elec}}\) is the power absorbed by the transmitter and receiver per bit in \(\mathrm{nJ/bit}\), \(\mathrm{E_{RX-elec}}\) is the power dissipated by the receiver during q-bits reception, and q is a bit-message. 2. The threshold energy (\(\mathrm{E_{T}}\)). A node with an energy value smaller than the threshold value will be removed from the CH selection process. Equation (4) is used to measure each node's threshold power (\(n\)): \[\mathrm{E_{T}}(n)=\mathrm{N_{adjacents}}*q*\mathrm{E_{elec}}+\mathrm{N_{ adjacents}}*q*\left[\mathrm{E_{elec}}+\ \beta_{\mathrm{fsm}}\right]*d^{2}\] (4) where the node energy threshold is represented by \(\mathrm{E_{T}}(n)\), the number of neighbouring nodes is represented by \(\mathrm{N_{adjacents}}\), the free space model is \(\beta_{\mathrm{fsm}}\), and the interval between transmitter and receiver nodes is represented by \(d\). Furthermore, each node (\(\mathrm{n}\)) sends _data_message_ with its ID and energy level to all adjacent WSN nodes, which is used to measure and update the adjacent WSN nodes table for each loop. 3. In each cluster, the mean distance (\(\beta\)) between candidate CH and its neighboring WSN nodes is important. If it is smaller, then the chances of selecting that nominated CH are higher.