Simulation results

In Figure 8, we compare the number broken links among AODV, PAODV, RB-MP, and RR-VMS. The velocity is set between 60 km/h and 80 km/h. Figure 9 shows the comparison of number of broken links under the speed range of 80 km/h - 120 km/h. In the freeway mobility model, a higher speed range results in a higher speed variation of each vehicle.

Simulation results show that the proposed RR-VMS performs better under a high speed range.

This means our VPS mechanism can reflect the stability of a vehicle even in a high speed range scenario.

Speed range: 60 km/h - 80 km/h

Figure 8. The number of broken links under a different number of vehicles with a low.

speed range.

As showed in the above figure, the number of broken link of AODV, PAODV and RB

random. The chosen rebroadcast can only ensure the reduction number of broken links in PAODV advantages of mobility prediction

rebroadcast nodes. Compared with PAODV, not restrict the number of rebroadcast nodes which are too close to the source

less help for routing, restrict the number of rebroadcast nodes, and select vehicles VPS as rebroadcast nodes.

above figure, the number of broken links of RR -AODV, PAODV and RB-MP. In PAODV, the rebroadcast node selection

rebroadcast node may not be the best choice. The selection mechanism reduction of hop count but not the stability of

in PAODV is more than that of RB-MP and RR

advantages of mobility prediction calculating the PHT (prediction holding time) Compared with PAODV, the stability is ensured. However, RM not restrict the number of rebroadcast nodes. RM-MP dose not eliminates

which are too close to the source node, too. In the proposed RR-VMS,

less help for routing, restrict the number of rebroadcast nodes, and select vehicles as rebroadcast nodes. Therefore, we have a better improvement.

the speed variation of vehicles is much more than that under the low speed range.

MP uses the previous speed and current speed of a vehicle to calculate the PHT.

Compared with mobility prediction, the proposed VPS can provide a long term observation of Speed range: 80 km/h - 120 km/h

number of broken links under a different number of vehicles speed range. less help for routing, restrict the number of rebroadcast nodes, and select vehicles with high Under the high speed under the low speed range.

of a vehicle to calculate the PHT.

a long term observation of different number of vehicles with a high

neighbors. So RR-VSM can determine the stability of a vehicle more under high speed range.

The delivery ratios under low and high speed range and Figure 11, respectively. If a routing path is broken,

Figure 11. Delivery ratio Figure 10. Delivery ratio

21

can determine the stability of a vehicle more precisely than RM

under low and high speed range scenarios are If a routing path is broken, transmitting packet

Speed range: 80 km/h - 120 km/h

. Delivery ratio under a different number of vehicles with a high speed range.

Speed range: 60 km/h-80 km/h

Delivery ratio under a different number of vehicles with a low speed range.

Number of vehicles

Number of vehicles

precisely than RM-MP

are showed in Figure 10 packets will be lost and the with a high speed range.

with a low speed range.

delivery ratio decreases. The result of number of broken links can reflect the result of ratio.

Figure 12 and 13 show the comparison of routing overhead

Figure 13. Rouintg overhead under a different number of vehicles with a high speed Figure 12. Rouintg overhead

22

The result of number of broken links can reflect the result of

show the comparison of routing overheadunder low and high speed ranges Speed range: 80 km/h - 120 km/h

Rouintg overhead under a different number of vehicles with a high speed range.

Number of vehicles Speed range: 60 km/h - 80 km/h

Rouintg overhead under a different number of vehicles range.

Number of vehicles

vehicles

The result of number of broken links can reflect the result of delivery

under low and high speed ranges. Rouintg overhead under a different number of vehicles with a high speed

different number of vehicles with a low speed

23

Note that the PAODV generates a lot of RERR because of the link breakage. Without restricting the number of rebroadcast nodes, RM-MP generates too many RREQ.

Nevertheless, RR-VMS reduce both the number of broken links and the number of control messages. In addition, RR-VMS improves the delivery ratio by using the VPS, so the routing overhead of RR-VMS is better than that of the other three approaches.

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Chapter 5 Conclusion

5.1 Concluding remarks

In this thesis, we have proposed a reliable routing scheme based on vehicle moving similarity (RR-VMS), which supports stable rebroadcast nodes selection and efficient route discovery to make inter-vehicle data transmissions more reliable. RR-VMS uses VPS (vehicle persistence score) to reflect the stability of neighbor vehicles. A vehicle with a high VPS, chosen as a rebroadcast node, will stay long enough in an inter-vehicle transmission path.

Moreover, to reduce the number of rebroadcast nodes, we define a donut-like selection area and restrict the number of rebroadcast nodes in order to reduce the route hop counts and network traffic. Simulation results have showed that RR-VMS can effectively enhance the reliability of routing paths and reduce control messages. The proposed RR-VMS improves (reduces) 11% (27%), 11% (25%), and 6% (16%) of the delivery ratio (number of broken links) compared to AODV, PAODV, and RB-MP, respectively. In addition, RR-VMS also reduces 26%, 20%, and 12% of the routing overhead compared to AODV, PAODV, and RB-MP, respectively. The proposed method can also be applied to other ad hoc routing protocols that involve broadcast to reduce the number of broadcast messages and to enhance the reliability of routing paths.

25

5.2 Future work

We may integrate a direction changing tracing mechanism to RR-VMS to make RR-VMS more suitable for an urban scenario as well. Moreover, we can make RR-VMS to be able to establish multiple paths that can provide a more reliable inter-vehicle transmission environment. In addition, we can combine streaming with our reliable routing mechanism to construct a more suitable environment for VANET streaming.

26

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