Many geographic routing algorithms have been proposed for vehicular ad hoc networks (VANETs), which have the\nstrength of not maintaining any routing structures. However, most of which rely on the availability of accurate real-time\nlocation information. It is well known that vehicles can be intermittently connected with other vehicles. Thus, in such\nnetworks, it is difficult or may incur considerable cost to retrieve accurate locations of moving vehicles. Furthermore,\nthe location information of a moving vehicle available to other vehicles is usually time-lagged since it is constantly\nmoving over time. Fortunately, we observe that the short-term future locations of vehicles can be predicted. Based on\nthe important observation, we propose a novel approach for geographic routing which exploits the predictive\nlocations of vehicles. Thus, we have developed a prediction technique based on the current speed and heading\ndirection of a vehicle. As a result, the request frequency of location updates can be reduced. In addition, we propose\ntwo forwarding strategies and three buffer management strategies. We have performed extensive simulations based\non real vehicular GPS traces collected from around 4,000 taxis in Shanghai, China. Simulation results clearly show that\ngeographic routing based on predictive locations is viable and can significantly reduce the cost of location updates
Loading....