# An Optimization Framework for Data Collection in Software Defined Vehicular Networks
## 4 Results
### Results on Optimization of Data Collection
As it is shown in Figure 10c, the latency for both the proposed method and the centralized architecture tends to decrease with the increment of the vehicular speed for both urban and rural mobility scenarios. However, for the autobahn mobility scenario, the latency for the proposed method essentially remains the same for the 0-50 kph and 90-250 kph ranges, where a slight increment can be observed in the transition from 50-90 kph. For the autobahn mobility scenario, the latency remains almost the same with variation in speed except at 0-50 kph. For all mobility scenarios for both data collection methods in hybrid and centralized architectures, the change in latency with vehicular speed is quite a bit lower compared to the change in cost, which is much higher. The highest latency gap between the data collection methods for hybrid and centralized architectures is for the rural mobility scenario, where there is about a 15 ms latency gap between the proposed method and the centralized architecture. Both the urban mobility and autobahn mobility scenarios have similar latency gaps (about 12.5 ms) between the proposed method and the centralized architecture. Furthermore, for all mobility scenarios, at all vehicular speeds, the proposed method's latency is much lower than the centralized architecture's latency as the lower limit of the 95% confidence interval of the centralized architecture's latency lies much above the upper 95% confidence interval limit of the proposed method, as evident from Figure 10c. However, for a given mobility scenario, the latency of the distributed SDVN architecture essentially does not vary with speed, and the latency values are much lower than those of both hybrid and centralized architectures. When analyzing the result on the packet delivery ratio variation with mobility in Figure 10d, the PDR for the centralized architecture has always been 100% and has always been higher than the proposed method for all speeds in all mobility scenarios. However,the important thing to note is that the proposed method has always achieved the 99.9% average PDR value for all speeds in all mobility scenarios, which is the minimum PDR required for vehicular communication applications. For the proposed method, the best PDR has occurred for the rural mobility scenario, in which the PDR has always been more than 99.95% and there has been an increasing trend in PDR with the increment of the vehicular speed for the rural mobility scenario. On the other hand, for the proposed method in the urban mobility scenario, PDR has been close to 100% at zero mobility conditions and has gradually decreased to 99.9% by 20 kph and then remained at 99.9% for the remaining vehicular speeds (20-60 kph). For the autobahn mobility scenario, the PDR has remained at 99.9% for the proposed method for 0-50 kph, and for subsequent higher speeds, PDR is higher than 99.9%, as evident from Figure 10d. The packet delivery ratio for the distributed architecture is confidently less than both other architectures under all speeds for urban mobility scenarios, and the average value for rural and autobahn mobility scenarios is close to 99%. For the urban mobility scenario, a decreasing trend for PDR of distributed architecture can be observed with an increment of speed, whereas for the rural mobility scenario, an increasing trend can be observed, and in the autobahn scenario, a clear relationship cannot be observed. The reason for the average communication cost per node per data-gathering cycle increment with mobility for data collection in centralized and hybrid architectures is that with high mobility, the probability for network topology change is high such that the number and type (vehicular or RSU) of neighbors of a given node can vary frequently. However, this increment in the probability of network topology change seems to have a lower impact on average channel utilization, average end-to-end latency, and packet delivery ratio for centralized and hybrid architectures.