# Clustering-Based Modified Ant Colony Optimizer for Internet of Vehicles (CACOIOV)
## 5 Evaluation
### Results and Simulation Analysis  
The outcomes of the simulation are presented and analyzed in this section, with the provided parameters used from Table 3. The interpretation of experimentations in this study are classified into five different categories for evaluating the performance of CACOIOV, ACO, AODV algorithms. In five different classes, parameters such as throughput, Data Packet Delivery Ratio (DPDR), number of  
Figure 4: Proposed Scenario. clusters, delay and packet loss are compared for these three algorithms with respect to the number of vehicles in the network. In this regard, we combined our proposed Algorithm 2 which is DA-TRLD with ACO and AODV algorithms to achieve realistic results by making a fair comparison. \(\bullet\) _Throughput:_  
This is the average rate of the data packets transmitted successfully over the IEEE 802.11P/5G communication channels' capacities. Figure 5 shows that the CACOIOV algorithm has better throughput than the other algorithms via a test of all number of vehicles. Besides this, the graph of ACO shows fluctuation of throughput when the number of vehicles increases. Also, by increasing the number of vehicles from 40 to 80, we notice throughput reduction for all these algorithms. Additionally, changing the number of vehicles from 40 to 200 has a negligible decrease on throughput of the CACOIOV scheme. We conclude that throughput will decrease by increasing the number of vehicles. \(\bullet\) _A  
Figure 5: Throughput. \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline Simulations Tool & NS2, SUMO \\ Mobility model & Freeway mobility \\ Radio Propagation model & TwoRayGround \\ Antenna model & Omni-directional \\ MAC layer Protocol & WAVE/IEEE 802.11p \\ Beam-forming technology & MmWave \\ The maximum size of packet in the queue & Priority queue (50 packets) \\ Interface Queue Type & Drop TailQueue \\ Population size (ants) & =number of vehicles \\ Node movement & Bidirectional \\ Maximum iterations & 150 \\ Grid size & 4 km\({}^{2}\) \\ Velocity & 22–30 m/s uninform \\ Number of network nodes & 40, 80, 120, 160 and 200 vehicles \\ Transport layer protocols & UDP \\ Traffic Type & CBR \\ Transmission range & Dynamic \\ Packet size & 512 bytes \\ Simulations run & 10 \\ Confidence interval & 95 \% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation Parameter of Protocols CACOIOV, ACO, and AODV. * _Data Packet Delivery Ratio (DPDR):_ This is a highly essential factor in measuring the routing protocol's performance in any network. Based on the various chosen parameters of the simulation, the protocol's performance is determined. The major parameters consist of the size of packet, number of nodes, range of transmission, and network structure. This metric shows successfully received packet ratio at destination. When the ratio of packet delivery is high, the performance appears to be better. The highest packet delivery ratio in Figure 6 belongs to the proposed algorithm. For all these algorithms we observed a fluctuation of _DPDR_ by increasing the number of vehicles from 40 to 160. In the case of increasing vehicles from 160 to 200 on the highway, we noticed an increase of _DPDR_. We can conclude that _DPDR_ will decrease by increasing the number of vehicles, especially when comparing the obtained results from with 40 vehicles and 200 vehicles. * _Packet Drop Ratio:_ The proportion of packets that never made it to the destination, compared to the originated packets at the source, is the packet loss ratio. The algorithm of the CACIOV shows that there is much less packet drop ratio during communication in comparison to the others as Figure 7 can clarify. We can clearly see huge differences in packet loss ratio between these protocols in all scenarios. Clearly, the packet drop ratio of CACIOV is 6 times less than AODV and 3 times less than ACO. Figure 6: Data Packet Delivery ratio. Figure 7: Packet Drop Ratio.