Stochastic Broadcast for VANET

1. Stochastic Broadcast for VANET Michael Slavik, ImadMahgoub Department of Computer Science and Engineering Florida Atlantic University 碩一 黃勝獅

2. OUTLINE • INTRODUCTION • STOCHASTIC BROADCAST • CONTINUUM PERCOLATION • SIMULATION RESULTS • CONCLUSION

3. INTRODUCTION • VANETs share a similar structure toMANETs so work can be adapted from that area • MANET routing protocols often include the need to broadcastinformation to the entire network • Broadcast packets leads to an exponential growth over timein the number of packets generated

4. INTRODUCTION • Several techniques have been proposed to reduce the number • These can be categorizedas counter-based, distance-based, location-based,clusterbased,and stochastic

5. INTRODUCTION • A broadcast protocol for VANET must have the followingproperties • Anonymous: • if node identity is not private, drivers willbe reluctant to adopt the technology because information including their location and speed will be traceable • Scalable: • a VANET potentially includes millions ofnodes and covers entire continent

6. STOCHASTIC BROADCAST • Stochastic broadcast directs each node to rebroadcast receivedmessages with some probability • This probability maybe fixed for all nodes or determined during runtime based onfactors such distance from the last hop neighbor

7. STOCHASTIC BROADCAST • No node identifiers are requiredto accomplish this so the scheme is private • All nodesmake decisions independently using local information, it isscalable

8. CONTINUUM PERCOLATION • Percolation is the study of random flow through a graph. • Here, nodes are placed in afield according to a Poisson point process with some intensityρ. • Nodes within a distance of r are then connected together(Figure 1)

9. CONTINUUM PERCOLATION • We assume homogeneoustransceivers with transmission radius r uniformly distributed in the plane with intensity ρ. • We use the notation to denote the expected number of neighbors for each node.

10. CONTINUUM PERCOLATION • continuum percolation it is known that there exists a critical density (λc) below which the network • Almost surely will be disconnected and above which will likely form an infinite connected cluster

11. SIMULATION RESULTS • The simulationrandomly distributes a given number of nodes in a field sized1000 x 1000. • One node is placed in the center that originatesa broadcast

12. SIMULATION RESULTS • All nodes are homogeneous with transmission radius 10 and the medium is collision-free. • A. Constant Retransmit Probability • B. Retransmit Probability by Distance

13. Fig. 2. Reachabilityvsλ for p = 1.0

14. Fig. 3. Number of messages transmitted vsλ for p = 1.0

15. Fig. 4. Reachabilityvsλp for constant p

16. Fig. 5. Number of messages transmitted vsλp for constant p

17. Fig. 6. Retransmit probability in Distance method

18. Fig. 7. Retransmit probability in Distance2 method

19. Fig. 8. Apparent retransmit probability for Distance methods

20. Fig. 9. Reachabilityvsλp for Distance methods

21. Fig. 10. Number of messages transmitted vsλp for Distance methods

22. CONCLUSION • we show that nodes can tune the performance of thebroadcast system to efficient levels by adjusting the retransmit probability • This discovery allows designers to overcome the distasteful dependency on vehicle density by estimating local vehicle density and setting the retransmit probability to a value