## 3 Self-Configuration Management (SCM)
### Data and Radio Model
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline \multirow{2}{*}{**Address**} & \multicolumn{2}{c}{\(\mathbf{S_{f}}\)} & \multirow{2}{*}{**T\({}_{\mathbf{C}}\)**} & \multirow{2}{*}{**TE**} & \multirow{2}{*}{**CP\({}_{\mathbf{1}}\)**} & \multirow{2}{*}{**CP\({}_{\mathbf{d}}\)**} & \multirow{2}{*}{**Memo**} & \multirow{2}{*}{**Status**} \\  & & & & & & & & \\ \hline
192.168.16.1 & & & & & & & Talk & Normal \\
192.168.3.2 & & & & & & Talk & Normal \\
192.168.5.3 & 11100000 & 170 & 84 & 249 & 415.60 & \(M4\) & Configured \\
192.168.3.5 & & & & & Talk & Normal \\
192.168.10.1 & 1000000 & 101 & 98 & 195 & 293.98 & \(M4\) & Configured \\
192.168.12.2 & 11000000 & 257 & 79 & 329 & 580.86 & \(M4\) & Configured \\
192.168.11.3 & 11100000 & 182 & 56 & 233 & 411.36 & \(M4\) & Configured \\
192.168.9.4 & 11110000 & 162 & 39 & 250 & 408.71 & \(M4\) & Configured \\
192.168.17.2 & & & & & Talk & Normal \\
192.168.20.1 & 1000000 & 200 & 66 & 261 & 457 & \(M4\) & Configured \\
192.168.2.2 & 11000000 & 128 & 95 & 219 & 344.44 & \(M4\) & Configured \\
192.168.16.3 & & & & & Talk & Normal \\
192.168.20.4 & & & & & Talk & Normal \\
192.168.14.5 & & & & & Talk & Normal \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary of primary nodes’ memos through the duty cycle for a number of the participating nodes. Figure 2: The SCM fault tolerance mechanism paralleling in actions of detection and configuring for the infected sensors. \[DA=\frac{\text{number of the alarm messages outgoing nodes that were injected in the round}}{\text{ participated nodes in the network through the round}}\% \tag{18}\]

Following simulation experiments, MATLAB R2019b was utilized to evaluate configuration parameters implemented by experiments. We evaluated the proposed network's efficiency in delivering data and verifying the network for defects. So, it was giving the specified networks a vast volume of temperature measurements from inner and outside sensors with varying ranges, examining whether or not alert messages appeared, and its ability to correct them. The study included configuration characteristics such as the distance between the sender head node and the receiving node, packet elapsed arrival time, packet size, transmitted node power level, detection latency, received signal strength, and successful/failed packet delivery. As shown in Figure 3, we implemented many datasets ranging in size from 16 to 1024 bits. Figure 3 depicts two charts describing signal strength in a large number of trials. Through the configuration technique, we obtained a high-bandwidth signal strength in the domain of the reaction speed term, which surpassed the signal strength generated by the phase of communication and error identification. We obtained excellent results for the values of the given configuration network parameters when compared to a comparable technique that investigated the configuration parameters on a similar sensor network [17]. We have calculated the costs of the transmission of the message through implementation, which is defined as the total time required to transfer a message over a network to the target destination comprising:

* Startup time (t): the time spent sending and getting nodes;
* Transfer time per bit (t\({}_{\text{b}}\)): This period includes all overhead costs that are determined by message length, error checking, and correction;
* Transit time per hop (t\({}_{\text{h}}\)): This period includes parameters like detection latency and network transmission delays. Figure 3: Illustrated are two plots of the received signal strength picking through different dataset samples to detect and configure, they are listed as **(a)** demonstration of the gained signal strength yielded after fault-configuration progress for various data samples injected in the radio and detection phase; **(b)** another plot is showed the synchronized coverage, and the produced signal strength of the faulty sensors by collaborating among the two phases throughout the synchronic implementation of the serial SCM model.