## 3 Spectrum Management for CR-VANET Using MCDM
### Channel Decision Based on Channel Ranking
#### 3.2.2 Qualitative Analysis for AHP
### TOPSIS Channel Ranking

TOPSIS channel ranking is used to eliminate the choice of choosing poor weights in terms of providing good qualitative data service to the channels. Enhanced TOPSIS helps to provide the best decision-making strategy for channel selection. TOPSIS with DAHP for Providing Qualitative Data Service

The ranking method can be followed in TOPSIS to enhance the weight of the decision matrix to choose a better channel for communicating. Combining DAHP with TOPSIS provides a better qualitative decision matrix for all data service applications. There are three steps to follow to provide better qualitative service in TOPSIS: channel properties collection, normalizing the decision matrix, and qualitative channel ranking. Table 9 depicts the simulation parameter of the proposed model by considering 20 to 200 channels in different weights and normalized values as shown in Equations (6) and (23), the below \(X(i,j)\) represented as matrix in Table 10:

\[X(i,j)=A(i,j)/\sqrt{\sum_{i=1}^{n}A_{ij}^{2}}\ (i=1,\ 2,\ \ldots,\ Until\ M) \tag{23}\] \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Text** & **Audio** & **Video** \\ \hline CDF & 0.15625 & 0.0960975 & 0.15625 \\ BW & 0.09375 & 0.1870143 & 0.21875 \\ PLR & 0.28125 & 0.1558453 & 0.09375 \\ Psig & 0.1875 & 0.2181834 & 0.0625 \\ Snoise & 0.21875 & 0.2805215 & 0.1875 \\ rmax & 0.0625 & 0.0623381 & 0.28125 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: DAHP qualitative order preference. Figure 4: Performance factor weight comparison with multiple scenarios. By implementing a rank-based channel selection process using DAHP-TOPSIS, all kinds of data services, such as text, audio, and video, are illustrated by comparing them with 20 channel ranks. In all CR-VANET scenarios, it is possible to communicate with various kinds of services, and channels 5 and 20 provide the best text, audio, and video data transmission by utilizing the optimized channel weight, and the same is represented as a table to display each channel and its rank in Table 19 as per Equations (13)-(15). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**CDF** & **BW** & **PLR



## 4 Performance Evaluation of DAHP-TOPSIS

### Performance Analysis by Calculating Computation Time

The proposed DAHP-TOPSIS methodology provides a better result by comparing other channel selection techniques, such as DAHP-SAW and random DAHP-MOORA. SAW and MOORA also can be integrated with DAHP to take channel decisions. SAW and MOORA are lightweight techniques to handle a smaller number of alternatives. Computation time and delay are much lower in the proposed techniques by comparing them with techniques and the comparative qualitative metrics mentioned in Table 20. The results of Table 20 are visualized in plots in terms of best, worst, and average cases, as shown in Figures 5-8. Figure 5: DAHP–TOPSIS for channel ranking. Figure 6: Best case computation time. Figure 7: Worst case computation time. ### Handoff Analysis in the Proposed DAHP-TOPSIS

The operational cost for handoffs is much costlier compared with other operations, especially in CR-VANET. By considering 20, 100, and 200 channels used to analyze the various spectra utilized in CR_VANET handoffs, comparative analysis of DAHP-TOPSIS, DAHP-MOORA, DAHP-SAW, and random helps to identify the best quality of service provided by CR-VANET in terms of average end-to-end delay, packet delivery ratio, packet loss ratio, and control overhead. Figures 9 and 10 depict the comparison of various channel selection respective handoff schemes for PU low traffic = 0.2 and PU high traffic = 0.6. Table 21 depicts the various handoff strategies by varying types of data, channel size, and traffic in PU, i.e., low = 0.2, high = 0.6. ## 5 Conclusions

OpenFlow-controlled CR-IoV enables efficient vehicular communication in high-mobility situations based on the scenario of vehicle direction, speed, and range in various handoff scenarios.