A Traffic Light Based Reliable Routing Protocol for Urban VANETs 都會區車載隨意網路下基於紅綠燈之 可靠 繞徑技術

1. A Traffic Light Based Reliable Routing Protocol for Urban VANETs都會區車載隨意網路下基於紅綠燈之可靠繞徑技術 指導教授：王國禎 博士 學生：張景喬 國立交通大學網路工程研究所 行動計算與寬頻網路實驗室

2. Outlines • Introduction • Background • Related work • Proposed traffic light based routing protocol • Simulation and discussion • Conclusion • Future work • References

3. Introduction • In urban vehicular ad hoc networks (VANETs), each vehicle (node) is independent and moves along the roads • VANETs are highly mobile wireless ad hoc networks • Due to high mobility in VANETs, wireless links would be disconnected frequently

4. Introduction (cont.) • Thus, routing paths may be very unstable due to network topology changes in VANETs • Broken routing paths cause the decrease of packet delivery ratio and the increase of end-to-end delay

5. Background • DSR (Dynamic Source Routing) [3] • Node-centric routing protocol • Main characteristics: • Route discovery • Route maintenance • Once a node receives a ROUTE REQUEST (RREQ) packet, if the node has not seen it before, it adds its node ID to the route and forwards the RREQ to its neighbors • If there is any broken link due to the network topology changes, source node can issue another RREQ to find a new route

6. Background • AODV (Ad-hoc On-demand Distance Vector) [2] • Source node broadcasts RREQ until the packets reach to destination node or intermediate nodes containing the routes to destination node • Once a node receives a RREQ packet, the node replies back to source node along the route • When a broken link is detected, ROUTE ERROR will be sent to source node by a node recently using this broken link, then the source node issues new route discovery

7. Background • The disadvantages of DSR [3] and AODV [2] [15]: • High velocity nodes result in very short window of communication between nodes on different streets • The built route expires quickly and the source node needs to re-issue new route discovery after sending only few data • When applied to urban environments, these protocols cause a high control overhead in terms of RREQ and RREP packets

8. Related work • CLA (ConnectionLessApproach) Routing [15] • No need to build routing tables to maintain the position of neighbor nodes • No need to maintain a hop-by-hop route between the source and destination nodes • The nodes belong to the selected cells can receive or forward data • When a relay node leaves the selected cell, it is no need to relay data

9. Related work • CLA • Streets are divided into cells

10. Related work • An example of CLA • RP: reference point

11. Related work • Disadvantages of CLA: • Cell A and cell C are located in road intersections where nodes would pass as fast as possible • A relay node would not relay data long enough, so a different node needs to be found frequently to relay data • In the selected cells, high speed nodes may be chosen if we do not set different backoff delays to nodes with different speeds

12. Related work • Road-based using vehicular traffic (RBVT) [12] • RBVT protocol utilizes real-time vehicular traffic information to create paths consisting of road intersections which may have network connectivity among them with higher probability • To reduce a path’s sensitivity to individual node movements, geographical forwarding is chosen to transfer packets between intersections on the path • RBVT does not consider the speed of nodes to forward data, so data loss may occur frequently

13. Related work

14. Proposed TLR • TLR (Traffic Light based Routing) • When vehicles stop at red traffic lights, nodes with no mobility can forward data to next nodes • Divide an area into numbers of virtual cells and traffic light cells • Select a list of virtual cells to be a packet forwarding path between source and destination nodes, and a traffic light cell is included in a virtual cell • Equipment required: • GPS (Global Positioning System) • Digital map

15. Proposed TLR • Virtual Cell ID: • Virtual cell IDs are specified on road intersections • Road intersections in urban areas usually have traffic lights • The red lights on means nodes must stop at the intersection • Using reliable and stable node to relay data packets may increase the packet delivery ratio

16. Proposed TLR • Example of specifying virtual cell IDs on road intersections:

17. Proposed TLR • A road intersection is divided into two cells: virtual cell and traffic light cell

18. Proposed TLR • Route discovery: • Source node broadcasts RREQ packets • RREQ packets contain <source node ID, destination node ID, sequence number, virtual cell record> • Virtual cell record contains a list of virtual cell IDs • When an intermediate node receives an RREQ packet, it attaches its current virtual cell ID into the virtual cell record and forward the updated RREQ

19. Proposed TLR • Route discovery: • If the destination node receives an RREQ packet then it records the following information to an RREP packet: • Current virtual cell ID of virtual cell ID record • Its direction • Sends the RREP packet back along the route • RREP packet contains <source node ID, destination node ID, sequence number, virtual cell ID record, destination direction>

20. Proposed TLR • Flowchart of a node forwarding a data packet from source to destination nodes

21. Proposed TLR • Flowchart of a node forwarding a data packet from source to destination nodes

22. Proposed TLR • Data forwarding procedure: • An algorithm for nodei receives a data packet from nodej: • If nodeiis a destination node, stop forwarding the data packet • If nodeiis not in the selected virtual cells, stop transmitting the data packet • Otherwise, nodei’s virtual cell IDis in the virtual cell ID record, and then computes backoff delay; if sensing no other nodes transmitting, then nodei transmits the data packet

23. Proposed TLR • Backoff delay computation of nodeireceiving a data packet: • For nodeiin a traffic light cell: where α is a random number in μseconds (0 ≦α < 51.2) ɣ is a delay threshold Spdiis the speed of nodei

24. Proposed TLR • Backoff delay computationof nodeireceiving data packet : • For noden in a virtual cell: where βis a random number in μ seconds (51.2 ≦β< 102.4) λis adelay threshold Distnmis a current distance between node n and previous node m MAX_DIST is a maximum radio range

25. Proposed TLR • Backoffdelay calculation:

26. Proposed TLR • An example of data forwarding:

27. Simulation and discussion • Packet delivery ratio [13]: Total number of packets successfully received from the destination node divided by total number of packets sent by the source node which generated by the CBR source • End-to-end delay [13]: This number indicates the average time measured in millisecondfrom the beginning of a packet transmission (including route acquisition delay) at a source node until packet delivery to a destination

28. Simulation and discussion • Simulation setting for GlomoSim [16]

29. Simulation and discussion • VanetMobiSim [14] parameters for road layouts[15]

30. Simulation and discussion

31. Simulation and discussion

32. Simulation and discussion • Simulation setting for GlomoSim[16]

33. Simulation and discussion • VanetMobiSim [14] parameters for road layouts [12]

34. Simulation and discussion

35. Simulation and discussion

36. Conclusion • We propose a traffic light based routing protocol for urban VANETs • Proposed TLR improves 10 % and 20 % of the packet delivery ratio compared to CLA and RBVT-P, respectively • Proposed TLR reduces 20 ms and 80 ms of the end-to-end delay compared to CLA and RBVT-P • Delivering packets to a relay node which is waiting for the red traffic light effectively improves the packet delivery ratio • The end-to-end delay can be reduced by the selecting stationary nodes as relay nodes and running backoff delay

37. Future work • Make the proposed TLR be able to establish multiple paths to provide a more reliable routing protocol for urban VANETs • Combine multimedia streaming with TLR to provide reliable multimedia for urban VANETs

38. References [1] Y. Toor, P. Muhlethaler, and A. Laouiti, “Vehicle ad hoc networks: Applications and related technical issues,” IEEE Communications Surveys & Tutorials, pp. 74–88, 2008. [2] C. E. Perkins and E. M. Royer. “Ad Hoc On-Demand Distance Vector Routing,” in Proc. 2ndIEEE Workshop on mobile comput. Syst. Appl., pp. 90-100, February 1999. [3] D. B. Johnson, D. A. Maltz, Y. C. Hu, J. G. Jetcheva, "The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks," in IETF MANET Working Group, INTERNET-DRAFT, 2 March 2001. [4] B. Parkinson and S. Gilber, “NAVSTAR: global positioning system – 10 years later,” in Proc. of IEEE, vol.71, no.10, pp. 1177- 1186, Oct. 1983. [5] M. Gerla, X. Hong, and G. Pei, “Fisheye state routing protocol (FSR) for ad hoc networks,” IETF Draft, 2002. [6] C. E. Perkins and P. Bhagwat., “Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers,” in Proc. of the SIGCOMM ’94 Conference on CommunicationsArchitectures, Protocols and Applications,pp. 234–244, August 1994.

39. References [7] P. Jaqcuet, P. Muhlethaler, T. Clausen, A. Laouiti, A. Qayyum, and L. Viennot, “Optimized link state routing protocol for ad hoc networks,” in Proc. of IEEE INMIC Multi Topic Conference, 2001. Technology for the 21st Century., pp. 62- 68, 2001. [8] S. Grafling, P. Mahonen, and J. Riihijarvi , "Performance evaluation of IEEE 1609 WAVE and IEEE 802.11p for vehicular communications," in Second International Conference on Ubiquitous and Future Networks (ICUFN), pp.344-348, 16-18 June 2010. [9] H. Hartenstein and K. P. Laberteaux, “A Tutorial Survey on Vehicular Ad Hoc Networks,” IEEE Communications Magazine, vol. 46, no. 6, pp. 164–171, June 2008. [10] A.H. Ho, Y.H. Ho, and K. A. Hua, “A Connectionless Approach to Mobile Ad Hoc Networks in Street Environments,” in Proc. of IEEE Intelligent Vehicles Symposium, 575 – 582, 2005. [11] P. Bose, P. Morin, I. Stojmenovic, and J. Urrutia, “Routing with guaranteed delivery in ad hoc wireless networks,” ACM Wirel. Netw., vol. 7, no. 6, pp. 609–616, Nov. 2001.

40. References [12] J. Nzouonta, N. Rajgure, A. Guiling Wang, and C. Borcea, “VANET routing on city roads using real-time vehicular traffic information,” IEEE Trans. Veh. Commun. pp. 3609 - 3626, 2009. [13] A. K. Pandey, H. Fujinoki, “Study of MANET routing protocols by GloMoSim simulator,” International Journal of Network Management, v.15 n.6, p.393-410, November 2005. [14] M. Fiore, J. Härri, F. Filali, and C. Bonnet, “Vehicular mobility simulation for VANETs,” in Proc. 40th Annual Simulation Symp., Mar. 2007, pp. 301-307. [15] Y. H. Ho, A. H. Ho, and K. A. Hua, “Routing Protocols for Inter-Vehicular Networks: A Comparative Study in High-Mobility and Large Obstacles Environments, ” Computer Communications Journal - Special Issue on Mobility Protocols for ITS/VANET 2008. [16] X. Zeng, R. Bagrodia, and M. Gerla, “GloMoSim: A library for parallel simulation of large-scale wireless networks,” in Proc. of 12th Workshop on Parallel and Distributed Simulations, pp. 154-161, 1998.