TBD: Trajectory-Based Data Forwarding for Light-Traffic Vehicular Networks

1. Jaehoon Jeong, Shuo Gu, Yu Gu, Tian He and David DuComputer Science and EngineeringUniversity of Minnesota{jjeong,sguo,yugu,tianhe,du}@cs.umn.edu TBD: Trajectory-Based Data Forwardingfor Light-Traffic Vehicular Networks June 23rd, 2009 IEEE ICDCS’09, Montreal, Quebec, Canada

2. Motivation • The vehicular networking is getting a hot research topic. • Internet Access, Driving Safety, Data Dissemination, etc. • The environments for the vehicular networks • Every vehicle has a DSRC device for wireless communication. • Every vehicle has a GPS-based navigation system for driving information. • The Internet Access Points (APs)are sparsely deployed in road networks. • The objective in this paper • The vehicles can deliver their packets to APs through the multi-hop forwarding with the help of other vehicles.

3. Problem Definition Light-Traffic Road Network Forwarding Path Carrier-1’sMovingTrajectory Delay-1 Carrier-2’sMovingTrajectory Next hop? Delay-1 <Delay-2 Delay-2

4. Problem Definition Road Network with Unbalanced Traffic Density Light Traffic Path Heavy Traffic Path Delay-1 Forwarding Path Next hop? Delay-1 >Delay-2 Delay-2 Heavy Traffic Path

5. Contribution and Challenges • Contribution • Data forwarding based on Vehicle Trajectory • With vehicle trajectory, TBD outperforms the existing scheme (VADD, Infocom’06) only using vehicular traffic density. • Challenges • A more accurate link delay model than VADD’s • Mathematical model for the link delay • End-to-End delay model based on vehicle trajectory • E2E delay modeling based on (i) vehicular traffic density and (ii) individual vehicle trajectory

6. Link Delay Model • Objective • To compute the expected link delay over a one-way road segment. • Road Segment for Link Delay Model • Given the vehicle arrival rate and the vehicle speed , • How to compute the Forwarding Distance ?

7. Forwarding Distance for Vehicle Arrivals Vehicle arrives at time . Forwarding Distance over Time Forwarding Distance

8. Forwarding Distance for Vehicle Arrivals Forwarding Distance Forwarding Distance

9. Link Delay Model Comparison between VADD and TBD • VADD Link Delay Model • Given the vehicle arrival rate and the vehicle speed ,the forwarding distance is the sum of the network components. • This model is inaccurate since it misses the following fact • Only the first network component can be used for data forwarding. • Performance Comparison • For Average Forwarding Distance, TBD is much closerto the Simulation resultthan VADD.

10. E2E Delay Model • Objective • To compute the expected end-to-end delay from a Vehicle to an Internet Access Point (AP). • Road Network Graph for Data Forwarding • Given a vehicle’s trajectory, • how to compute the E2E delay? • Since node1 and node2 have different trajectories, their E2E delays are different.

11. Expected Delivery Delayat Intersection (VADD Model) • :Expected Delivery Delay (EDD)at Intersection 1 • Where a packet is sent towards Intersection 2. Link Delay for Road Segment (1,2)

12. Expected Delivery Delayat Intersection (VADD Model) • Average Forwarding Probability ( ) • The probability that a packet at intersection i can be delivered towards neighboring intersection j. • We consider all the possible moving directions of the current packet carrier at intersection i. • How to compute ? Moving Direction-1 Moving Direction-3 Moving Direction-2 Packet Delivery Direction

13. Expected Delivery Delayat Intersection (VADD Model) • Limitation of EDD at Intersection • The vehicle trajectory is not used to compute the EDD. • Node1 and Node2 have the same EDD regardless of their different trajectories. • Thus, we cannot determine which node is a better next carrier. • How to involve the vehicle trajectory into EDD computation? • The main idea is to divide the delivery process recursively into two steps: • The packet forwarding process at the current carrier. • The packet carry process by the current carrier. They are very close to each other.

14. Expected Delivery Delay for Vehicle Trajectory (TBD Model) • Vehicle Trajectory: • Case 1: The packet is forwarded at intersection 1. • Case 2: The packet is carried to intersection 2 and is forwarded at intersection 2. • Case 3: The packet is carried to intersection 3 and is forwarded at intersection 3.

15. Expected Delivery Delay for Vehicle Trajectory

16. Forwarding Protocol • TBD Forwarding Rule • Within a connected component, packets are forwarded to the vehicle with a minimum EDD.

17. Performance Evaluation • Evaluation Setting • Performance Metric: Average Delivery Delay • Parameters: (i) Vehicular traffic density, (ii) Vehicle speed, and (iii) Vehicle speed deviation. • Simulation Environments • 36-intersection road network (4.2 miles X 3.7 miles) • Vehicle mobility model: Random-Way Point • Vehicle speed distribution: N(40,5) MPH • Communication range: 200 meters • Time-To-Live (TTL): infinite (i.e., no timeout)

18. Average Delivery Delay Comparison between TBD and VADD • TBD outperforms VADD under the light traffic, such 20~50 vehicles. • As the traffic density increases, two schemes are converged.

19. Conclusion • In this talk, the data forwarding scheme called TBD is introduced based on the vehicle trajectory: • Data Forwarding from Vehicle to AP. • Also, the link delay model is introduced for TBD data forwarding scheme: • This link delay model can be used for other VANET routing or forwarding schemes. • As future work, the multiple-hop Internet access will be investigated in the vehicular networks: • Vehicle trajectory will be used for the data forwarding for the Internet access.

20. Future Work: Reverse Data Forwardingfor Internet Access Target Point

21. Challenge in Reverse Data Forwarding • As packet destination, the vehicle is moving, not static. • The packet from AP needs to be delivered to the vehicle, considering the rendezvous point along the vehicle trajectory. • The reason of the target missing? • Inaccurate estimation of the vehicle arrival Target Point • How to provide this reverse forwarding? Target Missing!