## 4 Proposed mmWave Assisted CR-IoV
### Forwarding Zone Based Routing  
To enable data transmission among SUs, we present a novel FZ-MOWO approach. In IoV, there will be a large number of intelligent vehicles presented. Selecting optimal forwarders among a large number of vehicles is a time-consuming process that results in higher transmission delay. To avoid such delay, we introduced a novel forwarding zone concept in route selection. Whale optimization is the recent swarm-based optimization algorithm that solves multidisciplinary problems [54]. In this work, we utilized whale optimization for solving routing problems in IoV. Here, we have improved the whale optimization algorithm in two ways, including (i) formulating a new objective function by considering multiple objectives and (ii) minimizing computational time. Processing all SUs regardless of direction increases computational time. Thus, we first introduce the concept of FZ, which first finds the optimal FZ between the source (S) and destination (D) vehicles. Then, optimal forwarders are selected in the FZ region, as shown in Figure 6.  
Figure 5: 3D-Beamforming Process. The first step in determining FZ is to estimate the forwarding angle between \(\mathbb{S}\) and \(\mathbb{D}\). The forwarding angle (\(\psi\)) is estimated by the source node to determine FZ. The forwarding angle can be expressed as follows,  
\[\cos\psi=\frac{\mathbb{S}.\mathbb{D}}{\|\mathbb{S}\times\mathbb{D}\|} \tag{27}\]  
With this estimated angle, the FZ is created by the source node. Then, the proposed FZ-MOWO is executed with a new objective function to select optimal forwarding nodes. The mathematical model of the proposed routing algorithm is detailed below. **Initialization**--In this step, the possible solutions (vehicles presented within FZ) are initialized as the whales as [\(p=p_{1},p_{2},..,p_{n}\)]. **Fitness Evaluation**--For all whales in the population, the fitness function is evaluated. In this work, we have formulated a new fitness function, namely Potential Score (\(\rho_{S}\)), that is built upon multiple objective functions. The \(\rho_{S}\) is computed as the combination of Closeness (\(\omega_{C}\)), Direction (\(\omega_{D}\)) and Reliability (\(\omega_{R}\)). Here, \(\omega_{C}\) is computed as the function of Euclidean distance between the source and neighbor vehicle and \(\omega_{D}\) is the function of the moving direction of the neighbor vehicle (it is represented as 1 if both vehicles move in the same direction and 0 if both vehicles move in the opposite direction). The \(\omega_{R}\) is computed as the combination of multiple objectives such as forwarding probability, delay (\(\Upsilon_{dl}\)) and trust value (\(\Upsilon_{TV}\)). Forwarding probability (\(\Upsilon_{FP}\)) is computed as follows,  
\[\Upsilon_{FP}=\alpha_{1}\times\frac{v}{v_{max}}+\frac{\alpha_{2}}{CR} \tag{28}\]  
Here, \(\alpha_{1}\) and \(\alpha_{2}\) are the weight factors and \(v\) and \(v_{max}\) represent the current velocity and maximum velocity of the vehicle, respectively. The communication range is denoted as \(CR\). Delay is computed in terms of distance and queuing delay, while trust value is computed in terms of the number of successful packets transmitted through the candidate vehicle. By considering these factors, the reliability is computed as follows,  
\[\omega_{R}=\frac{\Upsilon_{FP}+\Upsilon_{TV}}{\Upsilon_{dl}} \tag{29}\]  
Then, the reliability factor is combined with the potential score as follows,  
\[\rho_{S}=\frac{\omega_{R}+\omega_{D}}{\omega_{C}}=\frac{\left(\frac{\Upsilon _{FP}+\Upsilon_{TV}}{\Upsilon_{dl}}\right)+\omega_{D}}{\omega_{C}} \tag{30}\]  
Figure 6: Proposed FZ model. For each solution in the population set, \(\rho_{s}\) is computed. Then, the best search agent (\(p*\)) is selected based on the fitness value. Based on this best search agent, the position of other solutions is updated. **Encircling Prey--**The whales can recognize and encircle the location of prey. This encircling process is carried out based on the selected best search agent.