## 3 Self-Configuration Management (SCM)
### Data and Radio Model
As a result of the sensor circuitry producing inaccurate data, we suggest the set S of sensor nodes is susceptible to inaccuracy. We presumed that all error-free sensor nodes in sensor networks measure the identical physical value at time t. With faults, WSN sensor nodes measure various physical quantities (data collected at time t by sensor node Si). The data model stipulates that for all healthy sensor nodes, the mean value M must be the same. However, the degree of unpredictable behavior--also known as misconduct or misbehavior--that different sensor nodes measure may differ. The premise in the WSN literature is that this sensor data pattern can spot malfunctioning sensor nodes. We propose that the set S of sensor nodes is subject to inaccuracy because the sensor circuitry generates erroneous data. It deployed S\({}_{1}\), S\({}_{2}\), and S\({}_{3}\) to the set of randomly selected sensor nodes suffering from zero blocking, one blocking, and random failures. Thus, the set of healthy sensor nodes present in the network is \(\mathbf{S_{H}}=\) S - S\({}_{F}\), where S\({}_{F}\subset\{\)S\({}_{1}\cup\)S\({}_{2}\cup\)S\({}_{3}\}\). Each sensor node verifies its group at the start of the radio communication phase by transmitting a pulse-of-life notification message that includes information about its heartbeat intensity, energy, transmission duration, and distance. It then produces data based on the surroundings where the sensor is being used. As a result, the data from the sensors that were fixed in accordance with the clusters of the designated network (C1, C2, C3... Cn) was provided. The data generated is evaluated to classify the information of the impulses sent, according to hypothesis H1, for which the CH credits the integrity of the node-set responses. While redundant impulses are categorized as hypothesis H2 (transient unstable impulses) and are regarded as system failures. H2 is another symbol for functional system disorder over discrete timescales. The error data concluded at the sensor node (\(E\)) are classified based on comparing accurate information coming from sensors of each cluster, and data of redundant and unstable sensors. Therefore, partial fault state coverage will be applied based on the faulted node's neighboring nodes S\({}_{\text{Negi}}\) from the received data \(X_{\text{j}}\). Fault detection was based on testing the former binary hypotheses. Let us hypothesize that hij has the binary decision (0 or 1) caused by testing information s\({}_{\text{i}}\) by S\({}_{\text{j}}\), where s\({}_{\text{i}}\)\(\in\) S and S\({}_{\text{j}}\)\(\in\) Negi. Accordingly, let us say that hij = 0 if the sensor node decides the error hypothesis H2, whereas hij = 1 if it comes true and hypothesis H1 and healthy data decide it. Algorithm 1 illustrated the distributed system-fault detection method at the CH level. ``` Input: Sensor position, Dx distance, transmission rang Rt, \(M\). Output: system fault status of sensor (\(f_{system}\)) Initialization phase  Each sensor Si\(\in\)S, each sensor discovers its neighbor S\({}_{\text{Negi}}\); and \(Si\) is considered a free fault sensor (Hardware physical composition is healthy) Radio phase For i = 1 to S do
1. Send a live-pulse message to CH synchronically;
2. CH delivers a periodic sensor message \(M\) and checks it timely \(t_{i}\);
3. CH establishes vector S\({}_{\text{healthy}}=\) S + S\({}_{\text{healthy}}\);
4. CH establishes vector S\({}_{\text{fully}}\)S + S\({}_{\text{fully}}\);
5. Conduct fault detection. Fault detection phase For i = 1 to S if S fails to respond within transfer time \(t_{i}\) CH set H2 in its memory \(S_{\text{fully}}=f_{system}+S_{\text{fully}}\) End else If M is incorrect information signals CH set H2 in its memory \(S_{\text{fully}}=f_{system}+S_{\text{fully}}\) End else CH set H1 in its memory \(S_{\text{fully}}=\) S + S\({}_{\text{healthy}}\) EndAfter the discovery phase, the CH would manage the network and should test the health of the network during its deployment.