## 3 Proposed Techniques
### Initial Phase
#### 3.1.2 Independent Nodes (INs)
Additionally, the Ns have been given the lowest energy cost values due to their data transmissions are confined within the cluster. After computing the routes costs, the SNI arranges its RT and chooses to send its data through the lowest cost route. During the round, the route costs of the RTs will dynamically change depending on the updated messages which are received from the NHIs. It is worth mentioning that the updated messages are sent periodically. Furthermore, the \(SNI\) continue sending its data through the lowest cost route. Thus, the DMR technique provides an approach, which is interested in transmitting the data through the shortest routes, either inside or outside the clusters according to the distances and the energy status of the nodes. Hence, the DMR technique introduces a cost equation for each available route in the source node. The source node sends its data through the route that has the lowest cost. For minimizing the energy load on the next hops, the DMR supposes that the RTs of the source nodes will be updated after receiving updated messages from their members. Based on the cost equation, the source node sends its data through the route that has the lowest cost after updating. By doing so, the DMR technique improves the equilibrium in the network and raises its stability. In addition, it reduces the amount of the energy consumption that is required for the data dissemination. ## 4 Simulation and Results

In this section, we evaluate the performance of the two techniques that we have proposed in this paper. The experimental results are compared with the ones obtained for the conventional LEACH protocol. Moreover, we extended the comparison to the very much related protocols: the IMHT-LEACH and the EDMHT-LEACH. A MATLAB program is used to evaluate the performance and to make the comparison. The common parameters, which are used in all experiments, are mentioned in Figure 2:1 Initially, we suppose that a fixed number of stationary sensor nodes are randomly scattered on three deployment areas that are different in terms of sizes and distances to the BS; The BS is located out of the sensors deployment area (Figure 8). Table 2 includes the essential parameters of the first experiment. Figure 9 represents the network lifetime for the three cases mentioned in Figure 2:2 Based on the obtained results, it can be noted that the two proposed techniques, SMR and DMR, achieved the longest network lifetime in all cases compared with the other protocols. The previous result has been achieved because the proposed approaches suppose that all the scattered nodes on the deployment area are distributed on more levels around the BS and the CHs. Particularly, the CHs and the INs determine their levels around the BS, whereas the Ns of each cluster will identify their levels based on the distances to its CH. Thus, all sensor nodes of the network use multi-hop routing to deliver the data to the destinations either the BS or the CHs. In addition, we have noted that the DMR has achieved a longer network lifetime compared with the SMR protocol in all cases. The reason that may be the base of this result is that the DMR technique allows to all the sensor nodes of the network to use different routes within any round. This way it reduces the energy load on the next hops if we compare it to the one that is produced if they stay using \begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Values** \\ \hline BS coordinates (\(X1\), \(Y1\)) & (150 m, 450 m) \\ Initial energy (\(Eo\)) & 0.5 \\ The percentage of \(CH\) (\(p\)) & 0.2 \\ Relative weight (\(a\)) & 100 \\ \(E_{disc}\) & 50 m/bit \\ \(\epsilon_{\delta}\) & 10 p/bit/m\({}^{2}\) \\ \(\epsilon_{mp}\) & 0.0013 p/bit/m\({}^{4}\) \\ \(T_{min}\) & 0.03 \\ Data aggregated energy (\(E_{DA}\)) & 5 nJ/bit \\ Control packet size & 200 bit \\ Data packet size & 6400 bit \\ \hline \end{tabular}
\end{table} 
Table 1: The common simulation parameters.