# A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach
## 6 Experimental Tests and Discussed Results  
The proposed scheme is implemented using the Opportunistic Network Environment (ONE) [33] simulator, a DTN-destined routing simulator for extendable VDTN routing; the proposed  
Figure 3: Hybrid Firefly–Glowworm VDTN solution flowchart. Swarm-VDTN router (Firefly-Glowworm) is compared to probabilistic DTN routing router namely ProPHET and a geographic VDTN protocol (GeoSpray). ProPHET protocol is available in ONE 1.4.1 version and GeoSpray is given for simulation by manuscript author Pr. [PERSON]. The Helsinki city shown in Figure 4 is set as ONE mobility model for the simulation tests. The latter return the major VDTN performance indicators which are:  
* Average latency: is calculated as the average end-to-end forwarding delay of all delivered bundles including the SCF time. * Delivery probability: returns the packet delivery ratio (PDR) including the number of generated copies. * Overhead ratio: which calculates the ratio between the number of generated undelivered copies and the number of delivered copies. * Number of flooded bundles: returns the total accumulated amount of replicated copies of all flooded bundles. * Number of dropped bundles: returns the total accumulated amount of lost copies of all flooded bundles. * Average hop count: the average length of traversed trajectories traversed by the delivered bundles between the corresponding source and destination nodes. Table 3 introduces the configuration settings set for the simulation tests of the proposed VDTN solution (Firefly-Glowworm). The simulations are tracked following equal back-to-back time intervals to evaluate the consistency limits of the swarm-VDTN router comparing to the comparison VDTN protocols. Figure 4: Simulation of Helsinki downtown mobility model. According to Figure 5, the swarm-VDTN generates reduced delivery delay comparing to GeoSpray and surpasses largely the probabilistic ProPHET. This can be justified by the effectiveness of alternated SCF vehicle selection using FA and GSO. According to Figure 6, the swarm-VDTN reaches close delivery probability ratios to the geographic VDTN routing (GeoSpray) while it surpasses regularly the probabilistic ProPHET model. This indicates  
Figure 5: Average delivery delay. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline VDTN simulator & ONE (1.4.1 version) \\ \hline Mobility scenario & Helsinki city model \\ \hline Simulated area’s size & 4.5 \(\times\) 3.4 Km \\ \hline Simulation time & 21,600 S (6 H) \\ \hline Number of vehicles & 50 nodes \\ \hline \multirow{2}{*}{Mobility models} & Cars & Shortest Path Map-based Movement \\ \cline{2-3}  & Buses & Bus Movement \\ \cline{2-3}  & Taxis & Map Route Movement \\ \hline \multirow{2}{*}{Vehicles speed ranges} & Cars & [10\(\sim\)52 Km/H] \\ \cline{2-3}  & Buses & [12\(\sim\)35 Km/H] \\ \cline{2-3}  & Taxis & [15\(\sim\)45 Km/H] \\ \hline Transmission range & 35 M \\ \hline Buffer size & 40\(\sim\)60 MBit \\ \hline Pause time & 20\(\sim\)120 S \\ \hline Bundle TTL & 30 Min \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Configuration settings of simulation tests. the utility of the implemented METD-based forwarding recovery mechanism when the hybrid FA-GSO fails in detecting better SCF vehicles toward every bundle's destination. According to Figure 7, the swarm-VDTN reduces considerably the number of distributed bundle copies especially comparing to ProPHET. Indeed, this aspect is the major advantage of the hybrid FA-GSO-based SCF vehicle selection, by restricting the flooding of bundles to nodes which offer optimized relay quality either geographically or probabilistically. According to Figure 8, the swarm-VDTN reduces ratio of routing overheads as a result of reduced bundles flooding results. Figure 6: Delivery probability. Figure 7: Number of flooded bundle copies. According to Figure 9, the swarm-VDTN shortens the forwarding trajectory to approximately the same levels of ProPHET surpassing the geographic model of GeoSpray.