GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless Networks
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Geographic routing in city scenarios
ACM SIGMOBILE Mobile Computing and Communications Review
Position-based unicast routing for city scenarios
WOWMOM '08 Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks
An efficient and robust data dissemination protocol for vehicular ad hoc networks
Proceedings of the 9th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
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Vehicular Ad hoc Networks (VANETs) are an emerging technology that allows vehicles to form self-organized networks without the need of permanent infrastructure. Communications in VANETs require the establishment of efficient routes between communicating vehicles. An efficient VANET routing protocol must be able to adapt to the frequent topology changes induced by high mobility. Most of the geographic-based VANET protocols rely on beacons for collecting neighbor nodes' information and to make position-based routing decisions. However, using beacons in routing decisions can cause performance deficiencies due to stale link-state information. In this paper, we present an efficient contention-based geographic routing protocol for VANETs, called Dual-Mode Optimum Distance (DMOD) routing protocol. DMOD is proposed to serve unicast messaging applications. The neighbor selection in DMOD is done opportunistically in collaboration with the neighbors depending on their distances from the destination. DMOD uses two distance computing modes in creating routing decision; greedy distance and driving distance. Forwarding decisions are built upon distributed contention process depending on the driving distances of the neighbors to the destination. If the driving distance method fails, greedy forwarding is used to explore further neighbors with better progress. Simulation results show that DMOD outperforms existing position-based approaches over a variety of network densities. DMOD can also improve packet delivery success ratio and reduce network overhead significantly.