1. Network Connectivity of VANETs in Urban Areas Wantanee Viriyasitavat, Ozan K. Tonguz, Fan Bai IEEE communications society conference on sensor, mesh and Ad hoc networks 89821006 鄭翔升

2. Outline  Introduction  Cellular automata-based traffic mobility model  Network connectivity in urban traffic  Conclusion

3. Introduction  Vehicular Ad Hoc Networks applications Safety relatedapplications non safety-related applications  It is essential to analyze and to have a complete understanding of the network topology and its connectivity pattern

4. Introduction  Static characteristics network connectivity path redundancy  Dynamic characteristics connection duration Re-healing time

5. Traffic model  Due to the unavailability of urban vehicular traffic traces  Cellular Automata (CA)-based vehicular mobility model Cellular road structure Vehicle movement Traffic light control

6. Traffic model  Cellular Road Structure for Manhattan Grid  evenly-spaced horizontal and vertical  two-lane,bi-directional streets  each lane is modeled as N cells  one vehicle per cell

7. Traffic model  Vehicle Movement  1. Vehicle’s state:  r n : street number where Vehicle n is located  D n : direction of travel of Vehicle n  x n and v n : the position and the speed  d n : distance to the vehicle in front of it  I n and s n are the closest intersection and the distance to that intersection  T n is the turning decision at the intersection I n

8. Traffic model  2. Algorithm for Updating Vehicle’s State  Case I: Go straightly Acceleration step Braking step : front car Randomization step : ??? Vehicle movement step : update  Case II: TURN red-light : stop green-light : right or left

9. Traffic model  Traffic Light Control  Cycle duration : green-red-yellow  Green light ratio  Signal offset between two consecutive intersections

10. Network connectivity  Two types of traffic: Non-transit Transit  Four categorized of traffic: Morning Rush Hour traffic Lunch Time traffic : low transit Evening Rush Hour traffic Midnight traffic : high speed

11. Network connectivity  Two different network characteristics corresponding to two types of application  Static characteristics Network connectivity : reachable of safety messages Path redundancy  Dynamic characteristics Connection duration Re-healing time

12. Network connectivity  Static characteristics of network connectivity  Network connectivity : Two vehicles can be connected either directly or indirectly (via a multi-hop route)  Path redundancy between two vehicles – the maximum number of (either node- or edge-) disjoint paths between two connected vehicles.

13. Network connectivity  network connectivity statistics averaged over 100 simulation runs Network typeDensity (veh/km 2 ) Average network connectivity Very sparse4068.12 Moderately sparse6097.97 Sparse8099.71 Moderate160100 Dense240100 Highly dense320100

14. Network connectivity  Average 20 neighboring vehicles => network connectivity 100%  network connectivity is less than 80% in a very sparse network (40 veh/km 2 )  Disconnected network problem may become a serious problem during the initial deployment of intelligent vehicles

15. Network connectivity  Path redundancy statistics

16. Network connectivity  number of redundant paths increases with the traffic density  But does not necessarily decrease with distance  Roughly 20 copies of the same message  8 more on the intersection  In most cases, more than one path available between them

17. Network connectivity  Dynamic characteristics of network connectivity  Number and duration of connected periods  Re-healing time – the duration of time during which two vehicles are disconnected

18. Network connectivity  Even in 80 veh/km 2 dense network, the connectivity between two vehicles lasts for less than 6 minutes on average.  These statistics become much worse when traffic density decreases 10 sec in 40 veh/km 2 network

19. Network connectivity  Re-healing time

20. Network connectivity  8 seconds of re-healing time in a very sparse network  less than 3 seconds in a dense network

21. Network connectivity  The bipolar behavior : connect ? not evenly distributed  Broadcast storm problem becomes much more severe in a moderate or highly dense network  Path redundancy Multi-path routing protocols

22. Conclusion  Cellular Automata (CA)-based mobility model analyzed the network connectivity pattern of urban traffic  serious disconnected network problem  bipolar behavior is observed where both the broadcast storm and the disconnected network problems coexist