# An Effective and Efficient Adaptive Probability Data Dissemination Protocol in VANET
## 3 Effective and Efficient Adaptive Probability Data Dissemination Protocol (EEAPD)
### EEAPD Protocol Description
This results in low vehicle density in each road segment (Refer to Figure 8). As specified in Equation (2) holding time is inversely proportional to the distance from source nodes to receivers' nodes. Therefore in Figure 6a. (vehicles o, p, q, r, t, v, and n) belonging to the farthest road segment are assigned to the minimum \(W_{t}=0\delta\). (Vehicles l and m) belong to the same slot must wait for \(1\delta\) where (vehicles j and k) have to wait for for \(2\delta\), (vehicles h and i) have to wait for \(3\delta\), and (vehicles a, b and c) have to wait for \(4\delta\) prior to transmitting. This value (\(\delta\)) is an important time factor that makes it responsible for a node to wait from when it receives the data packet to before it decides to retransmit to other nodes. According to this mechanism, only members' vehicles allocated to the last slot on transmission range will be chosen as unique forwarder vehicles. Therefore, assigning a different timer to different slots contains nodes will help to minimize the broadcast problem. In spite of that, in a dense area where there is a large number of vehicles allocated to the same slots with the same given timer the problem can happen. As found in Figure 6a. at the same time (vehicles o, p, q, t,  
Figure 6: The system model for EEAPD, (**a**), Many vehicles at the last road segment; (**b**), Few vehicles at the last road segment. and v) immediately will rebroadcast the received data packets. In this case, no collision can happen. But the problem will occur if a number of nodes allocated in the same slots becomes high. Figure 8: The relationship between vehicle density, redundancy ratio and the probability of rebroadcast. Figure 7: The Dalian University of Technology area, (**a**) real world map; (**b**) standard map. To handle this complicated situation, an efficient and effective method of computing the rebroadcasting probability, namely \"\(P\)\", was designed. EEAPD has the ability to work without the need for beacon exchange (neighbor vehicles information) but it only considers enclose vehicle density. The probability, given by Equation (3), is the association of present redundancy ratio values \"\(r_{i}\)\" computed at dispatch time, and preceding one, named \"\(r_{prec}\)\" by including the preceding computed probability \"\(P_{prec}\)\" for the final sent data packet. The motivation behind this relationship is to control the redundancy ratio. \[P_{1}=\frac{2}{r}.P_{prec}=\frac{2}{r_{0}}.\frac{2}{r_{prec}}=\frac{2}{r_{0}}. \frac{2}{r_{1}}\ldots\frac{2}{r_{i-1}}.\frac{2}{r_{i}}=\frac{(2)^{r+1}}{\Pi_{k =0}^{i}r_{k}} \tag{3}\]  
Thanks to EEAPD, as shown in Figure 6b, the vehicle (\(k\)) found in the last road segment was selected to rebroadcast the received message. Due to that, there are many road segments in the transmission range and the last slot found that there is only one node needed to rebroadcast the message. It is shown that the lower the number of vehicles the smaller the number of duplicate messages. Therefore, these increases rebroadcast probability opportunity as shown in Figure 3:0 In Figure 8, the probability of a vehicle to forward a data packet is opposite to both the redundancy ratio and the number of vehicles. Hence, the road segment which has a large number of vehicles will diminish the vehicle's satisfaction with being a forwarding node.