Practical location-based routing in vehicular ad hoc networks

Rapid advancement in wireless communication has made it possible to develop vehicular ad hoc networks, in which a vehicle can communicate with other vehicles via a wireless, multi-hope fashion. A variety of appealing real-world applications can be enabled by VANETs, such as driving safety and urban monitoring. Many location based routing algorithms have been proposed for data delivery in VANETs. Most of them assume that accurate location information is available when needed. In practice, however, such assumption is unrealistic. It incurs considerable cost to retrieve location information. In addition, a vehicle is on the fast move over time, and a location previously obtained may become invalid after certain time. This paper proposes a routing algorithm that is based on a practical location information model. To solve the problem of location inaccuracy and vehicle mobility, we devise a location predictor which estimates the possible location of a vehicle by using history information. Based on the greedy forwarding strategy, the proposed routing differentiates packets in terms of closeness to destination and jump distance. We evaluate the performance of the proposed algorithms with a large real trace of taxi motion in Shanghai. Trace-driven simulation results demonstrate that data delivery performance is improved.

[1]  Amin Vahdat,et al.  Epidemic Routing for Partially-Connected Ad Hoc Networks , 2009 .

[2]  Hari Balakrishnan,et al.  Cabernet: vehicular content delivery using WiFi , 2008, MobiCom '08.

[3]  Martin Mauve,et al.  MobiCom poster: location-based routing for vehicular ad-hoc networks , 2003, MOCO.

[4]  Timur Friedman,et al.  DTN routing in a mobility pattern space , 2005, WDTN '05.

[5]  Kevin R. Fall,et al.  A delay-tolerant network architecture for challenged internets , 2003, SIGCOMM '03.

[6]  Brad Karp,et al.  GPSR: greedy perimeter stateless routing for wireless networks , 2000, MobiCom '00.

[7]  Martin Mauve,et al.  A routing strategy for vehicular ad hoc networks in city environments , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[8]  Brian Gallagher,et al.  MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[9]  S. Yousefi,et al.  Vehicular Ad Hoc Networks (VANETs): Challenges and Perspectives , 2006, 2006 6th International Conference on ITS Telecommunications.

[10]  Paolo Bellavista,et al.  Mobeyes: smart mobs for urban monitoring with a vehicular sensor network , 2006, IEEE Wireless Communications.

[11]  Hariharan Krishnan,et al.  Performance evaluation of safety applications over DSRC vehicular ad hoc networks , 2004, VANET '04.

[12]  Martin Mauve,et al.  Location-Based Routing for Vehicular Ad-Hoc Networks , 2002 .

[13]  Lionel M. Ni,et al.  SEER: Metropolitan-Scale Traffic Perception Based on Lossy Sensory Data , 2009, IEEE INFOCOM 2009.

[14]  Sidi-Mohammed Senouci,et al.  GyTAR: improved greedy traffic aware routing protocol for vehicular ad hoc networks in city environments , 2006, VANET '06.