## 6 Simulation and Results Discussion  
In this section, the performance of the CD-ICC protocol that is presented in the aforementioned sections has been evaluated in terms of successful transmission probability, e2e delay, duty cycles, and average power transmission. In the simulation, random topology has been considered, where sensors are randomly distributed in \(3.5\times 3.5\) square area with normalized distance, the number of sensors are fixed in this area. The destination is located at the origin (0, 0), and correspondence source sensor located at \((d_{sd},0)\), in addition, the number of relay sensors are varying and randomly deployed between source and destination. The SINR threshold \(\gamma_{thd}\) is set to be 0 dB. The pseudo code of the CD-ICC based on IEEE 802.15.6 policy and numerical parameter used in this paper given in Algorithm 1 and Table 3, respectively. Figure 3, shows the comparison of successful transmission probability of the DTM, and CD-ICC protocol as a function of \(d_{sd}\) and \(\sigma\). The important results appeared in the figure:  
1. In the case of \(\sigma>0\) dB the successful transmission probability is vary, which it is reduced at the short distances and increases at large distances this is due to signal fluctuations become more at \(\sigma>0\) dB. 2. Even at large distance (greater than normalized threshold distance '1'), we get successful transmission probability less than 0.7. 3. The proposed protocol shows better successful transmission probability at the short and large distance compared to DTM. 4. For the low values of \(\sigma\) correspond to small variations of the signal power and high values of \(\sigma\) corresponding to stronger power variations. 5. At distance \(d_{sd}\) = 2, and \(\sigma=9\) dB, the successful transmission probability increased by 1.6 times over DTM. Further, At the distance \(d_{sd}\) = 2, and \(\sigma=7\) dB, the successful transmission probability increased by 5 times over DTM. While, At distance \(d_{sd}=1.5\), anda \(\sigma=5\) dB, the successful transmission probability increased by 13 times over DTM. ```
0:\(d_{sd}=0.1:0.1:3.5\), \(scal=\text{random}\ (1,\ \text{length}(d_{\text{sd}}))\), \(\xi_{max}\), \(\gamma_{thd}\), begin
0:for\(d_{sd}\)
0:for\(\mathbf{z}=1:1:\text{length}(d_{\text{sd}})\)
0:\(d_{sr}=scal\ (z)\ast\ d_{sd}(z)\)
0:\(d_{rd}=scal\ (z)\ast d_{sd}(z)\)
0: Select \(\xi_{min}\in\text{random}\ [0,\ 7]\)
0: Calculate back-off time given in (27)
0: Calculate \(R_{ate}\) given in (30)
0: Calculate time as
1:\(T_{x}=\frac{number\ of\ bits\ of\ x}{R_{ate}}\)
1: Calculate e2e delay given in (19)
1: Calculate duty cycle given in (31)
1: Calculate average power consumption given in (32)
1: Endfor
```  
**Algorithm 1**CD-ICC Pseudo Code. Figure 4, shows the comparison of successful transmission probability of the CD-ICC protocol as a function of \(\xi_{min}\). The important results appeared in the figure: As the \(\xi_{min}\) increases, the successful transmission probability required is rises, in order to transmit the critical data efficiently. We can also note from Figure 3 that as the inter-nodes distance of \(S-R\) and \(R-D\) links are decreases, the successful transmission probability is increased. \begin{table}
\begin{tabular}{c c} \hline \hline Frequency band [MHz] & 402–405 (MICS) \\ Bandwidth [MHz] & 1 \\ Maximum transmission rate \((R)\) [Kbps] & 75.9 \\ Threshold transmission rate \((\beta_{o})\) [Mbps] & 1 \\ Modulation & DPSK \\ Payload size [bits] & 2000 \\ Minimum contention windows \(CW\)min [slots] & 16 \\ Maximum contention windows \(CW\)max [slots] & 64 \\ SINR threshold \((\gamma_{thd})\) [dB] & 0 \\ MAC header [bits] & 56 \\ MAC footer [bits] & 16 \\ PHY header [bits] & 32 \\ RF transceiver power on \((T_{on})\) [s] & 2 \\ Short interframe spacing time TpSIFS [\(\upmu\)s] & 50 \\ Preamble [bits] & 88 \\ Slot time Ts [\(\upmu\)s] & 125 \\ Delay time \(\alpha\) [\(\upmu\)s] & 1 \\ Maximum critical data index \(\xi_{max}\) & 7 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Numerical parameters.