GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Location-aided routing (LAR) in mobile ad hoc networks
Wireless Networks
Fair sharing of bandwidth in VANETs
Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems
Computer Communications
Algorithms and Protocols for Wireless Sensor Networks
Algorithms and Protocols for Wireless Sensor Networks
Practical metropolitan-scale positioning for GSM phones
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
An efficient neighborhood prediction protocol to estimate link availability in VANETs
Proceedings of the 7th ACM international symposium on Mobility management and wireless access
Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey
Wireless Personal Communications: An International Journal
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Vehicular Ad Hoc Networks (VANETs) have been widely studied, and the deployment of such networks is likely to happen soon as the required technology and commercial opportunities are already available. Most of applications proposed for these networks require a localization mechanism with reasonable accuracy. In addition to applications, most protocols rely on the availability of a system that determines vehicles' positions. As many vehicles are (or are in the process of being) equipped with GPS, the accurate localization of vehicles in VANETs is achievable. However, one issue that has been ignored is the localization of neighboring vehicles. In VANETs, nodes usually move at high speeds; the information about the position of a neighbour vehicle is therefore fast outdated. The naïve approach for handling this issue is to increase the frequency by which periodic messages containing a node's position are exchanged. This solution might lead an unfeasible overhead significantly dropping the bandwidth available for the exchange of services' data. In this paper, we study this problem further, and propose a solution where vehicles predict the position of a neighbor for the near future. Through extensive experiments, we show that a prediction model of low complexity was able to considerably increase the accuracy of neighbor localization. Our mechanism has achieved an accuracy of 50 centimeters with a frequency of exchange of beacons 75% smaller than the naïve approach.